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Join our vibrant research community and learn from leading researchers.

At the ANU College of Engineering, Computing and Cybernetics, you will join a dynamic and pioneering research environment where you can pursue your interests alongside some of the world’s brightest and most innovative researchers. You’ll get an opportunity to collaborate with an extensive network of academic, government, and industry partners in Australia and worldwide, and gain the skills to enable change in today’s complex world.

Research at the College affords opportunities to undertake study in several research areas – each offering dynamic and diverse research opportunities producing internationally significant outcomes. Research is conducted in our three Schools: the  School of Computing ,  School of Cybernetics , and  School of Engineering .

We offer two Higher Degree by Research (HDR) degrees:

• Doctor of Philosophy (PhD)
• Master of Philosophy (MPhil)

Both degrees are advanced research-focused degrees that produce high-quality original research under the supervision of world-class academics and vibrant intellectual leaders.

Come and join our research community!

Explore our Research Programs

Master of Philosophy

A 2-year program of research to produce a thesis.

Doctor of Philosophy

A 4-year program of research to produce a thesis that makes a significant contribution to the field.

More Information

Pre-application process

Formal Application

Scholarships

Additional Awards

We have 15 Computer Science PhD Projects, Programmes & Scholarships in Australia

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Computer Science PhD Projects, Programmes & Scholarships in Australia

Adaptive control of hypersonic systems, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Funded PhD Project (Students Worldwide)

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Immersive technology (AR and VR) for heart surgery

Competition funded phd project (students worldwide).

This project is in competition for funding with other projects. Usually the project which receives the best applicant will be successful. Unsuccessful projects may still go ahead as self-funded opportunities. Applications for the project are welcome from all suitably qualified candidates, but potential funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

PhD in Machine Learning: Unlocking the Future of Cardiovascular Medical Diagnostics

Detecting threats in temporal networks - optima phd (australian citizens only), thrive: finishing school well, understanding the ecological and evolutionary effects of heatwaves in tropical species and ecological communities, hydrogen degradation in silicon solar cells and modules, application of safety data analytics to extract knowledge from fdm database, enhancing aviation wildlife management under climate change crisis based on data analytics and machine learning techniques, low-power long-range (lora) wireless sensor network for smart cities., computational rna biology phd: crispr functional genomics and long-read nanopore sequencing, phd scholarship in quantum-safe security measures for iot-based intelligent transport systems, developing dynamic line rating determination of transmission lines using artificial intelligence techniques, development of automatic control systems for integrated microfluidic chips used in mrna vaccine manufacturing, geotechnical assessment of ground settlement and soil-structure interactions based on data analytics and machine learning techniques for sensor-driven smart highways.

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Apply for Doctor of Philosophy - Computing

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Doctorate by research

• Qualification Doctor of Philosophy - Computing

The Commonwealth Register of Institutions and Courses for Overseas Students (CRICOS) Code indicates a registered program offered to international students studying in Australia on student visas.

The Curtin campuses or teaching locations where units of this course are offered.

As a doctoral research degree candidate, you will uncover new knowledge either by the discovery of new facts, the formulation of theories or the innovative reinterpretation of known data and established ideas. Your research will use an in-depth understanding of theories and concepts to develop practical solutions for real-world problems.

A higher degree by research differs from other postgraduate degrees in that at least two-thirds of the study program must involve research. Although some coursework units may be required, the main part of your work will be in the form of a thesis written under the guidance of a supervisor and associate supervisor(s). Your thesis must, in the opinion of the examiners, be a substantial original contribution to the knowledge or understanding of any field through the discovery of new facts, the formulation of theories or the innovative reinterpretation of known data and established ideas. It must also demonstrate your capacity to conceive, design and complete independent research.

Throughout your studies, our faculties will provide you with access to equipment and resources to support your research, and financial assistance to attend appropriate local and international conferences.

Please refer to the handbook for additional course overview information. 

Why research at Curtin

Curtin is widely recognised for applied research firmly focused on solving real-world problems. Underpinning our research endeavours are strong partnerships with industry, business and government, which result in outcomes that greatly benefit the broader community locally, nationally and globally. Our international reputation for being a strong partner in industry-driven research ensures our graduates enjoy outstanding opportunities to become innovators in their fields.

What you'll learn

• demonstrate expert understanding of theoretical knowledge and to reflect critically on that knowledge and their practice
• think critically, evaluate existing knowledge and ideas, undertake systematic investigation and reflect on theory and practice to generate original knowledge
• apply expert creative, technical and professional skills to the field of work or learning
• explain and critique theoretical propositions, methodologies and conclusions
• present a complex investigation of originality or original research for external examination against international standards
• communicate complex research concepts, plans and outcomes to the general community, peers and the national and international research community
• design, implement, analyse, theorise and communicate research that makes a significant and original contribution to knowledge and/or professional practice

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Professional recognition

Depending on your area of speciality, you may be eligible for membership of various professional organisations upon graduation.

Admission criteria

What you need in order to get into this course. There are different pathway options depending on your level of work and education experience.

Entry requirements for Australian and New Zealand students

Applicants are required to demonstrate a capacity to carry out independent research and have adequate training and ability to pursue the proposed research course. Generally, this may be a master degree or bachelor degree with first or upper second class honours. See the Section 3.2.1 of the  HDR admission policy  for detailed information.

English requirements

Curtin requires all applicants to demonstrate proficiency in English. Specific English requirements for this course are outlined in the IELTS table below.

You may demonstrate English proficiency using the following tests and qualifications .

IELTS Academic (International English Language Testing System)

Overall band score

Use your experience to get credit towards your degree

Finish your course sooner with credit for your previous study or work experience.

Fees and charges

Fee information is not available for this course at this time. Find estimated course fees .

Looking for more detail on the course structure?

For start dates, please view the  academic calendar .

All endeavours are made to ensure location information for courses is up to date but please note they are subject to change.

The University reserves the right to withdraw any unit of study or program which it offers, to impose limitations on enrolment in any unit or program, and/or to vary arrangements for any program.

How to apply

Please review information on how to apply for the campus of your choice

• Curtin Perth

Please note that each campus has different application deadlines. View our application deadlines page for further information.

The offering information on this website applies only to future students. Current students should refer to faculty handbooks for current or past course information.

The information on this page may be subject to change. In particular, Curtin University may change the content, method or location of delivery or tuition fees of courses.

While Curtin uses reasonable efforts to ensure that the information provided on this page is accurate and up to date, errors and omissions sometimes occur. Curtin makes no warranty, representation or undertaking (expressed or implied) nor does it assume any legal liability (direct or indirect) for the accuracy, completeness or usefulness of any information.

View courses information disclaimer .

• Curtin course code:  DR-COMPTG
• CRICOS code:  043987G
• Last updated on:  19 June 2024

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Bachelor of Business Administration (BBA) Specialisations

Business specialisations available in the BBA:

• Accounting for Business Decisions Specialisation
• Business Law and Policy Specialisation
• Business Project Management Specialisation
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Specialisations available from Humanities and Science:

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Business specialisations:

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Bachelor of Innovation Specialisations

Specialisations available from Humanities, Science and the Centre for Aboriginal Studies:

• Biological Diversity Minor
• Climate Change Science Minor
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• Food Science Minor
• Forensic Studies Minor
• Geophysics Minor
• Geospatial Technology Minor
• Go Global – Internship Specialisation 1
• Go Practice – Internship Specialisation 1
• Indigenous Australian Cultural Studies Specialisation
• Landscape Restoration Minor
• Mapping and Land Planning Minor
• Metallurgy Minor
• Mining Minor
• Optimisation Minor
• Strategic Studies Specialisation

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• Programs and Courses

Doctor of Philosophy, ANU College of Engineering and Computer Science

A single four year research award offered by the ANU College of Engineering and Computer Science

• Length 4 year full-time
• Minimum 192 Units
• Academic plan 9070XPHD
• Post Nominal
• CRICOS code 048353A
• Engineering and Related Tech
• Ms Erin Maplesden
• Admission & Fees
• Introduction

Employment Opportunities

Career options, learning outcomes, further information.

• Additional Information

Admission Requirements

Scholarships.

• Indicative Fees

Program Requirements

As a PhD student you will work with increased independence, under the direction of an expert academic supervisor or a supervisory panel. Your research will make an original and important contribution to human knowledge and may be published in scientific journals or presented at international conferences.

The Doctor of Philosophy usually involves three to four years of full-time study or the part-time equivalent and requires the submission and successful examination of a thesis of up to 100,000 words.

To be eligible for admission to the Doctor of Philosophy program you should have completed a relevant four-year undergraduate degree from an eligible university, or a postgraduate qualification with a significant research thesis component. There must be a supervisor at the ANU College of Engineering and Computer Science who is available and willing to supervise your research, and you must have identified a research project.

Admission to a Doctor of Philosophy degree at ANU requires:

1. An Australian Bachelor degree with at least Second Class Honours - Upper (First Class Honours is often required) or its international equivalent, or

2. Another degree with a significant research/thesis component that may be assessed as equivalent to paragraph (1), or

3. A combination of qualifications, research publications and/or professional experience related to the field of study that may be assessed as equivalent to paragraph (1).

All applicants must meet the University’s English Language Admission Requirements for Students .

You may be eligible for admission if you can demonstrate that you have significant research experience and a background equivalent to these qualifications.

The ANU College of Engineering and Computer Science encourages prospective students to take a self assessment test to determine their suitability for admission/scholarship before completing the pre-application process .

If you think you might qualify, you can also check out our guide on how to apply .

Indicative fees

For more information see: http://www.anu.edu.au/students/program-administration/costs-fees

For further information on International Tuition Fees see: https://www.anu.edu.au/students/program-administration/fees-payments/international-tuition-fees

Fee Information

All students are required to pay the  Services and amenities fee  (SA Fee)

The annual indicative fee provides an estimate of the program tuition fees for international students and domestic students (where applicable). The annual indicative fee for a program is based on the standard full-time enrolment load of 48 units per year (unless the program duration is less than 48 units). Fees for courses vary by discipline meaning that the fees for a program can vary depending on the courses selected. Course fees are reviewed on an annual basis and typically will increase from year to year. The tuition fees payable are dependent on the year of commencement and the courses selected and are subject to increase during the period of study.

For further information on Fees and Payment please see: https://www.anu.edu.au/students/program-administration/fees-payments

ANU offers a wide range of  scholarships  to students to assist with the cost of their studies.

Eligibility to apply for ANU scholarships varies depending on the specifics of the scholarship and can be categorised by the type of student you are.  Specific scholarship application process information is included in the relevant scholarship listing.

For further information see the  Scholarships  website.

Exceptional research degrees at ANU

The Australian National University provides PhD students with a vibrant research community and outstanding program support. When selecting a research program, an institution's reputation is everything. ANU is one of the world's leading universities, and the smart choice for your research program.

The ANU College of Engineering and Computer Science (CECS) has a track record of exceptional performance: a strong international research reputation based on a culture of excellence; a vibrant research-led education programme; and strong contributions in policy advice and community engagement.

We conduct research and teaching that aims to deliver solutions to some of the most pressing technological and environmental challenges the world faces, recruiting and nurturing students and academics who will lead the way in finding solutions to these challenges. The college has an extensive network of international collaboration with research institutions and industries in Europe, the Asia Pacific and the USA, as well as locally.

As a PhD student you will work with increased independence, under the direction of a supervisory panel of experts in the field. Your research will make an original and important contribution to human knowledge, research and development.

ANU ranks among the world's very finest universities. Our nearly 100,000 alumni include political, business, government, and academic leaders around the world.

We have graduated remarkable people from every part of our continent, our region and all walks of life.

We have research opportunities in a wide range of fields across engineering and computer science. Career options following completion of a Doctor of Philosophy include many opportunities in addition to an academic path such as research opportunities in industry or commercialisation of your research through a start-up.  

Some of our alumni hold positions as company directors, chief technology officers, senior managers, and consultants to major industry bodies and organisations in Australia and internationally.

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Learn more about the degrees offered at the ANU College of Engineering and Computer Science, read current student profiles to see what campus life is really like, and discover what our graduates have achieved since leaving the College at Visit the College of Engineering and Computer Science website.

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School of Computing and Information Systems

Computer science.

Computer Science has a long tradition of excellence at Melbourne. The arrival of Australia’s first computer to Melbourne in 1956 form the roots of our current computing research, which still examines how to realise the full potential of computer technology.

Our main strands of research balance theoretical and applied, established and new fields of exploration. Current areas of excellence include programming languages, algorithms, distributed computing, and cybersecurity and cryptography.

Research Themes

Effective data structures and algorithms optimise the performance of any computer program. Computer science has a number of continuing areas of interest including text information retrieval (search) technology, text indexation and compression, and the analysis of big data.

Databases and Information Retrieval

Databases is the study of efficient storage, retrieval, and management of large data, whereas information retrieval is the process of accessing and extracting relevant information from the databases.

Distributed Systems and Cloud Computing

Our world-leading distributed computing research group is pushing the boundaries of how we can extract more performance and computer-power from large-scale networks of computing devices. Fog, edge, cloud and grid computing issues are a continuing focus of our distributed computing work.

Programming Languages and Formal Verification

We work on designing and implementing programming language and formal verification tools and techniques that enable the development of high-assurance trustworthy software.

Quantum Computing

Quantum computing focuses on developing computer technology based on the principles of quantum theory, which explains the nature and behavior of energy and matter on the quantum (atomic and subatomic) level.

Security and Privacy

We are working on novel and practical solutions to improve the security and privacy of large real-world systems. Our research includes both attack and defense approaches that work on different layers, from web APIs, ML models, core software libraries to micro-architecture, firmware and hardware.

Software Engineering

Software Engineering is a multidisciplinary field which focuses on the systematic design, development, testing, and maintenance of software applications and systems. Research areas within this theme encompass topics such as software quality assurance, agile methodologies, program repair, and human and social aspects of software engineering.

Groups, Labs and Centres

Melbourne eresearch group (meg).

The Melbourne eResearch Group (MEG) supports the development, support and delivery of research-oriented IT systems to a wide range of research communities at the University of Melbourne. We provide research-oriented software engineering using a combination of the current bleeding edge technologies through to more tried and trusted software solutions.

Cloud Computing and Distributed Systems (CLOUDS) Laboratory

The CLOUDS Lab is a software research and development group engaged in the design and development of next-generation computing systems and applications that aggregate or lease services of distributed resources depending on their availability, capability, performance, cost, and users' quality-of-service requirements.

• Academic Centre of Cyber Security Excellence (ACCSE)

Our research capability is focused on key challenges, including detecting attacks in large, complex systems, using formal methods to design platforms that are resilient to attack, designing robust controllers for critical infrastructure, and providing a legal framework for the governance of cyber operations that span a range of jurisdictions.

While machine learning bots reduce the burden on human analysts by filtering information, cybersecurity poses unique challenges for human-bot teams. This project aims to develop rigorous science for human-bot cybersecurity teams, with the goal of developing cohesive teams that are robust to active human and machine learning adversaries.

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Doctor of Philosophy (PhD) in Computing, Information Technology or Mathematical Sciences

Undertake a phd in computing, information technology or mathematical sciences.

Analyse the past or reprogram the future

• Utilise technology to improve pest management.
• Improve security of digital health information systems.
• Design statistically based programs for computer aided diagnosis of breast cancer.

Undertake a Computing, Information Technology or Mathematical Sciences research-based higher degree at Flinders, and you’ll have the opportunity to explore some of the biggest unanswered questions of our time.   

Research supervisors 

How to apply 

Enquire 

Doctor of Philosophy (Information Technology)

Duration: 4  years

Delivery mode: In Person

Location: Bedford Park

CRICOS code:  106272F

Annual fees: 2024: $40,700

Further information on fees listed

Doctor of Philosophy (Mathematics/Statistics)

CRICOS code:  003371D

Master of Science (Information Technology)

Duration: 2  years

CRICOS code:  106284B

Master of Science (Mathematics/Statistics)

Delivery mode: On campus

CRICOS code:  002644C

Doctor of Philosophy (Mathematics/Statistics) / Master of Business Administration (Future Business)

Duration: 5  years

Delivery mode: In person

CRICOS code:  113547C

Annual fees: 2024 MBA (Future Business): $59,200 2024 PhD (Mathematics/Statistics): $40,700

Doctor of Philosophy (Information Technology) / Master of Business Administration (Future Business)

CRICOS code:  113546D

Annual fees: 2024 MBA (Future Business): $59,200 2024 PhD (Information Technology): $40,700

Why undertake a PhD in Computing, Information Technology or Mathematical Sciences at Flinders

• Complete your research under the supervision of nationally and internationally recognised scientists
• Access Flinders at Tonsley, where computer science, information technology and mathematics are co-located with the highly esteemed Medical Device Research Institute , as well as some of Adelaide's biggest businesses and industries
• Boost your expertise and career prospects, and become an expert in your area of specialisation
• Apply your research to the real world with Flinders’ expansive network of industry, government and scientific partners
• Utilise Flinders’ cutting-edge equipment and state-of-the-art facilities
• Join the university that produced Australia’s Fields Medal winner, Professor Terence Tao.

PhD opportunities

With the guidance of an expert supervisor, take the opportunity to leverage Flinders’ extensive industry connections and plug into our $120 million hub of innovation and entrepreneurship at Tonsley.  

Your chosen research area is flexible, and ultimately agreed between you and your supervisor. Areas of focus could include:

• Computer Science and Information Technology
• Cybersecurity

Digital Health

• Mathematics
• Industry 4.0
• Or other area of interest in consultation with your supervisor.

You will drive a project that creates valuable new scientific knowledge; finding solutions that will help to build a healthier, prosperous and more secure Australia.

Analyse the past or reprogram the future. Join us to pursue your passion, develop advanced research skills, explore multi-disciplinary problems and seek impactful answers to well-defined problems.

Your career

A PhD in Computer Science, Information Technology or Mathematical Sciences will position you as an expert in your area of specialisation. A PhD is a stepping stone to professional research or as a highly sought-after expert in the private or public sector in Australia or internationally. This prestigious degree will equip you with valuable skills in communications, time management and organisation transferrable to any role.

Potential occupations include:

• Professional researcher
• Consultant or advisor
• Project manager
• Senior or lead statistician, analyst etc.
• Science writer

Potential employers include:

• Lockheed Martin
• BAE Systems Australia
• SAAB Australia
• Department of Science and Technology (DST)
• Australian Space Agency
• Universities
• Government agencies including security, commerce and health
• Research centres

Research Centres and Institutes

Medical device research institute.

The Medical Device Research Institute (MDRI) aims to develop innovative solutions to a range of healthcare problems including: new assistive technologies to make rehabilitation more engaging and build independence for people living with impairments; developing personalised models and new medical devices to improve surgery successes and big data to better understand Australian health. To achieve this, we are bringing great minds together; engineers and clinicians, health researchers and web developers, designers and users, industry and government to collaborate on creative solutions to address global healthcare challenges.

Find out more

Flinders Digital Health Research Centre

The Flinders Digital Health Research Centre, concentrates on projects developing and deploying computational solutions which provide benefits to the management of health in numerous social and clinical settings, including home and workplace. Our emphasis is on empowering individuals through customising and personalising health information and processes. Projects cover a wide range of technical areas in health informatics including cybersecurity, data management and analysis, human-computer interaction, health software, messaging and terminologies, mHealth and social media and telehealth.

Potential research supervisors

Flinders academic staff are recognised experts in their specialised Computing, Information Technology or Mathematical Sciences fields. They are embedded in real-world applications of research, with extensive knowledge, networks and industry partners to support PhD students and deliver exciting and valuable research outcomes.

Get in touch with a supervisor of your choice today, to discuss your area of interest, and start on your path to thought leadership.

Dr Saeed Rehman

Learn what to prepare before approaching a potential research supervisor.

Ready to find the perfect supervisor for your research journey?

Explore Research @ Flinders.

Cybersecurity and Networking

HCI, Simulation and Visualisation

Knowledge Discovery, AI and Data Mining

Mathematical Analysis

How to apply

Review the course rule

Check your eligibility

Find a research supervisor

Find out about scholarships and fees

Prepare your application

Enquire now

If you have a question about how to apply, please review our Frequently Asked Questions before submitting an enquiry.

For all other course enquiries complete the enquiry form.

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Graduate Research

Doctor of Philosophy - Engineering and IT

• Arrow-right #2 in Australia for Engineering and Technology
• Arrow-right #50 in the world
• Course code: DR-PHILEIT

Course overview

Make your own research contribution with the Doctor of Philosophy (Engineering and IT) at Australia’s leading university*. Build your expertise in a specialist area and be supported by experienced supervisors and advisory committees to create significant change in society. You’ll demonstrate academic leadership, independence, creativity and innovation in your research work.

Research projects are offered in:

• Biomedical engineering
• Chemical engineering
• Computing and information systems
• Electrical and electronic engineering
• Infrastructure engineering (civil engineering; structural engineering; environmental engineering; geomatics and spatial information)
• Mechanical engineering and mechatronics.

You can also pursue an engineering or IT research project of your own.

* Times Higher Education World University Rankings 2023

Graduate Research Showcase

Find out how to study a research degree, come along to our in person Graduate Research Showcase on 31 October at Melbourne Connect.

Learn more and register now

Solutions for global problems

Work alongside researchers who are creating technological solutions to significant problems in our society and in our future. You’ll benefit from an environment of cross-disciplinary research excellence at Melbourne, connecting diverse study areas and blending academic and industry.

Our researchers are looking into water resource management, clean energy, disaster management, climate change, cancer treatment, epilepsy suppression, food processing, automated interpretation of data, personalised medicine, smart grids and more.

Internationally recognised qualification

Be part of one of the largest engineering research institutions in Australia, measured on research income. You’ll receive strong backing from industry and government.

Joint PhD degree opportunities

In addition to our leading PhD program, we also offer several graduate research joint PhD initiatives. Our joint PhD programs access expertise, resources and world-class training at the University of Melbourne and a leading institution abroad.

Our Jülich-University of Melbourne Postgraduate Academy (JUMPA) is a multidisciplinary Joint PhD training program with the Jülich Research Centre, Germany.

Our Melbourne-CNRS Network is a multidisciplinary Joint PhD training program with the Centre National de la Recherche Scientifique, France.

Our Melbourne India Postgraduate Academy (MIPA) is a Joint PhD training program with one of three top Indian Institutes of Technology (IITs): IIT Madras, IIT Kanpur, and IIT Kharagpur.

Our Melbourne and Manchester Graduate Research Group is a multidisciplinary Joint PhD training program with the University of Manchester, United Kingdom.

Our Priestley Scholarships are offered in conjunction with University of Birmingham .

For further information and how to apply for joint PhD programs: Graduate research: Joint PhDs

World class facilities

We’re home to an Australian-first, state-of-the-art VR biomechanical facility, CAREN (Computer Assisted Rehabilitation Environment), which focuses on improving our understanding of human movement and rehabilitation. You’ll also have access to cutting-edge laboratories and a heavy engineering workshop for materials testing, engine and turbine testing, wind tunnel investigations and metal forming processing.

Related study areas

• Bioinformatics
• Civil, structural and architectural engineering
• Computer science
• Data and analytics
• Data science
• Digital infrastructure engineering
• Engineering
• Engineering business and management
• Environment
• Environmental engineering
• Information systems
• Information technology
• Information technology and computer science
• Mechanical, aerospace, industrial and mechatronic engineering
• Software engineering

PhD (Computer Science) - Apply

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Research Training Scheme

See admissions

AU$36,480 (2024 annual)

Prepare your application

Before you can apply for a research program at RMIT you must complete a number of steps to prepare your application.

• Find out how to prepare your application for a research program at RMIT

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For further information on application and acceptance deadlines for the upcoming intake, please refer to  International Application Dates .

Support options for this degree

Find more about how to prepare your expression of interest and application for research at RMIT.

Discover fee information for research degrees at RMIT.

Get the financial support you need while you undertake your research projects with a research scholarship tailored for your needs.

Helpful step-by-step how to apply guides, including everything you need to submit an application to RMIT - from entry requirements to the documentation you'll need to complete your application to selection tasks and more.

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Achieve your study goals with a scholarship. Each year scholarships are awarded to new and continuing international students across RMIT study areas.

The School of Graduate Research can help answer questions about fees, scholarships, how to apply or find a research supervisor.

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RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Luwaytini' by Mark Cleaver, Palawa.

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business.

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• Doctor of Philosophy

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Fees and scholarships.

Learn more about the fees that apply to you for this course. For fee type definitions and further assistance, see the Fee Calculator Help page. You can also search our database for scholarships that are relevant to you or this course.

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There is no current fee information available for this course. Please visit the fee calculator to browse course fees from a previous year, or other courses.

Scholarships

Postgraduate scholarships  support UWA's position as one of Australia's leading research-intensive universities and the premier research institution in WA.

Research Training Program

Cost of living, international student fees, admission requirements.

If you’re interested in furthering your career by studying this postgraduate degree, find out the admission details below.

Admission Requirements

Approval for admission to a PhD requires an applicant to demonstrate that they have sufficient background and experience in independent supervised research to successfully complete the course. It also requires the University to ensure that appropriate supervision and resourcing are available. Applicants are required to demonstrate that they have met the requirements of the University Policy on: Adequate Research Preparation and any other requirements for admission of the University, and— (a) have a bachelor's degree of this University or equivalent qualification; or (b) (i) have previously undertaken work of a sufficiently high standard towards a higher degree by research in this or another approved institution but not have submitted it for any degree; and (ii) have completed an appropriate PhD research proposal;

A student who wishes to undertake a PhD in the field of creative writing must, in addition, submit a substantial folio of published creative work, normally in the form of one or more books.

Prior to enrolment,  all applicants are required to demonstrate that they have met the University’s English language requirements . 

English competency

English is the language of instruction and assessment at UWA and you will need to meet the University’s English language requirements  to be eligible for a place.

How to apply

Ready to join us?

Find out how to apply through our online application portal.

We’ll guide you through the application process including important steps, entry pathways and documents you’ll need.

Course details

About the course, quick details.

• Perth (Crawley campus)
• By agreement with their supervisors, students may commence at any time throughout the year, except December.
• Full-time students are expected to spend at least 30 hours per week on their research throughout the year. Part-time students are expected to spend at least 15 hours a week on their research throughout the year.
• 003310F - Human & Behavioural
• 003311E - Science (Paramedical)
• 003312D - Science (Physical and Biological)
• 003314B - Computer Science
• 003316M - Laws
• 003317K - Engineering
• 003318J - Education
• 003319G - Economics & Commerce
• 003320D - Arts
• 003321C - Architecture
• 013797F - Science (Geology and Physical Geography)
• 024816F - Agriculture (Agricultural Economics, Plant & Soil Sciences)
• 024818D - Agriculture (Animal Science)
• 037146K - Dentistry (Public Health)
• 037147J - Dentistry (Biological Sciences)
• 037148G - Dentistry (Paraclinical Sciences)
• 037149G - Dentistry (Clinical)
• 037157G - Medicine (Public Health)
• 037158F - Medicine (Biological Sciences)
• 037159E - Medicine (Paraclinical Sciences)
• 037160A - Medicine (Clinical)
• 055301K - Mathematics
• 058936F - Human and Social Geography
• 4 years full-time

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Doctor of Philosophy

A Doctor of Philosophy (PhD) is an internationally recognised graduate research program that will enable you to become an independent researcher. 

With the guidance of an advisory team, you'll undertake a research project, produce an 80,000-word thesis and complete an oral examination.

A PhD takes 3 to 4 years full-time. Under guidance, you'll develop advanced research skills and knowledge in your chosen field.

The thesis is a substantial document that makes an original contribution to your field of research. Your thesis may involve an alternate format .

You'll need a strong academic background and you may need to submit a research proposal and other documents to support your application. About 1,000 PhD candidates join UQ each year researching a wide range of topics.

Research at UQ

UQ is one of Australia’s top research-intensive universities. Our research makes an impact on the world's cultural, environmental, economic and social challenges.

Learn more about UQ's research

Program highlights

• Be inspired and challenged to explore new ideas and develop greater understanding of complex questions with leading researchers.
• Access premier resources including one of Australia’s largest libraries, with more than 2 million physical resources and 116,800+ journal subscriptions.
• Foster and improve your skills through the Career Development Framework, created with industry.
• Learn from researchers whose work addresses national and global cultural, environmental, economic and social challenges.

35 in the world

CWTS Leiden Ranking 2023

51 in the world

Academic Ranking of World Universities 2023

Supervision

You have to find and contact a thesis supervisor before you apply

This supervisor will support, guide and mentor you through your research, and can introduce you to professional networks that will start your career.

Find a supervisor

3-Minute Thesis

The showcase event for research candidates is the 3-Minute Thesis (3MT). 

3MT is held each spring.

Learn more about the 3MT

Career development

UQ offers a range of development opportunities via the Career Development Framework (CDF) to help you develop portable skills for any career or industry.

Learn more about the CDF

Studying at UQ gave me the flexibility to expand my knowledge across different areas of science outside of my chosen specialty. Keeping my scientific and translational skills broad has allowed me to adapt to different environments and opportunities throughout my career.

Discover Postgraduate Molecular Biology

Discover Postgraduate Geographic Information Science

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Entry requirements, gpa equivalent.

Select where you studied and your qualification to see the GPA you need to be considered for this program.

Meeting the GPA requirement doesn’t guarantee admission.

Academic entry requirements

You have to prove you are prepared for PhD study. You do this by showing you:

• have completed some research experience
• have completed an approved university degree  and
• can meet the English language requirements.

Approved degrees

An approved degree needs to be:

• in an area relevant to your proposed PhD project and
• completed no more than 10 years ago.

You need one of the following approved degrees to apply for a PhD:

• Master of Philosophy (or another research master’s degree); or
• Bachelor’s degree from an approved university with at least honours class IIA or equivalent; or
• Coursework master’s degree with an overall grade point average of 5.65 on the 7-point UQ scale which includes relevant research experience, approved by the dean; or
• Postgraduate degree (at least one year full-time or equivalent) with an overall grade point average of 5 on the 7-point UQ scale, together with demonstrated research experience equivalent to honours class IIA will be considered on a case-by-case basis; or
• Bachelor’s degree plus at least 2 years of relevant research experience , including research publications.

Research experience

You'll meet the requirements for admission into a PhD in terms of 'research preparedness' if you can provide evidence that you've planned and executed project work and/or a body of research with some independence.

To demonstrate this, we'll ask you to provide one of the following:

• with completed courses that aim to develop research skills (minimum value of #1 unit e.g. 50 per cent of a #2 unit course), and/or
• the completion of a supervised research project that includes an individually graded written report with a combined minimum course volume equal to #4 units at UQ.
• Scholarly papers involving a substantial contribution as an author, appearing in recognised academic journals or in volumes published by recognised academic publishers.
• Research or technical reports prepared for industry, government or business, which adhere to the broad conventions of academic publishing (i.e. contain an up-to-date review of relevant literature, a description of relevant research methods and an evaluation of results, etc.) and which identify you as a significant contributor.
• A portfolio of published creative work together with published critical discussion of some or all of that work, or of a comparable body of work by others, and which demonstrates your development of a scholarly approach to creative work as research investigation.
• Demonstrable industry or work experience where you can demonstrate that you have planned and executed a project, working with a high level of independence.

Student visas

International students who are accepted into full-time study in the Doctor of Philosophy are eligible to apply for an Australian Student visa (subclass 500).

This program has two CRICOS codes:

• 0100213 – Architecture, creative arts, education, health, information technology, management and commerce, mathematical sciences, social and cultural studies
• 0100214 – Agriculture and environmental studies, dentistry, engineering, human movement, medical studies, natural and physical sciences, pharmacy, psychology, veterinary science

Discuss your proposed project with us to determine which CRICOS code is most relevant for your visa application.

There are a number of requirements you must satisfy before a visa is granted, including the genuine temporary entrant (GTE) requirement.

Learn more about student visas

Additional entry requirements

Many departments will have additional entry requirements and may request documents to support your application, such as a research proposal. You should discuss these additional requirements with your potential thesis supervisor.

Additional application information

Minimum English language proficiency requirements apply, please refer to the English proficiency policy .

English language requirements

There are a few ways you can meet our English language requirements. If you sit a test, the following scores are needed for PhD admission:

Read our English language requirements

Scholarships

There are several types of PhD scholarship:

• tuition fee scholarship : this covers the fees charged by UQ for PhD study
• living stipend scholarship: this is a   fortnightly payment (or stipend) to support your daily expenses
• top-up scholarship: may be provided by external organisations, supervisors, or philanthropic donations. When awarded, they provide an additional payment on top of a living stipend scholarship. They cannot be held without a living stipend scholarship.

Each year, we award more than 600 scholarships to attract and support the highest quality higher degree by research applicants.

View all postgraduate research scholarships

University scholarships

UQ scholarships include:

• Graduate School Scholarships
• Graduate School Tuition Fees Scholarship
• Aboriginal and Torres Strait Islander Scholarships
• Earmarked Scholarships
• The Graduate School Scholarship

Other scholarships

Throughout the year we advertise a range of other research scholarships, including top-up scholarships, travel grants and external scholarships, including:

• Westpac Future Leaders Scholarship

How to apply for a scholarship

You can apply for many scholarships using the same form as your PhD application. External scholarships might have different ways to apply. 

Our Scholarships website explains how to apply for each scholarship. If you are applying for a non-UQ scholarship, outcome dates may vary.

Fees and costs

Tuition fees.

Your fees will vary according to your academic field, study load and whether you study internally or remotely.

Learn more about postgraduate research fees

Research costs

The department you enrol with will meet all necessary costs for your project, including:

• resource and facility costs: at UQ, which may include other organisations in Australia or overseas
• travel costs: to complete fieldwork, collect data, or to visit libraries or other repositories
• coursework costs: for courses studied outside the department
• relevant training: in particular methodologies or techniques.

How to apply

Before you apply, 1. check your eligibility.

Check your eligibility by reviewing the entry requirements for UQ's Higher Degrees by Research. If applying for a scholarship, check the scholarship's eligibility and important dates.

2. Approach a potential supervisor or find a project

You'll either need to find:

• a supervisor in your field who will support your proposed project.  Identify a researcher .
• a project you can join that suits your interests.  See available projects .

If you're choosing a researcher, you'll need to find one with relevant expertise and get agreement to support your PhD and project.

Many departments will require additional information to make a decision around your motivation, understanding, commitment, and financial support required.

They may request documents to support your application, such as a research proposal. You should discuss these additional requirements with your potential thesis supervisor.

3. Gather your documents

You will need to compile the necessary documents. We will accept scanned copies of original documents, but you will have to keep all original documents for the duration of your studies.

Upload all documents as PDFs and name your files like this: LASTNAME_firstname_document-name.pdf

If any of your documents is in a language other than English, you will need to send both the original document and an official translation.

Send the following documents with your application:

An academic CV assists us to determine your readiness to commence a higher degree by research. For the purposes of this application, your academic CV should be current (i.e. no more than 6 months old) and include information under the following headings:

Personal details

• your full name
• your contact details (phone number, email address, city and country of residence)
• nationality
• languages spoken and proficiency level for each
• your ORCID ID or other research output identifier (such as Google Scholar) if you have one (see the ORCID ID and research identifiers information provided by UQ Library).

As the purpose of this academic CV is to determine your academic suitability for a higher degree by research program at UQ and your competitiveness against other applicants, we only require information that is of direct relevance to our decision-making processes. With this in mind, please do not include the following in your academic CV:

• photographs/head shot
• marital status
• driver’s license
• date of birth/age
• hobbies and interests.

Educational qualifications and academic awards

List each of your formal educational qualifications in reverse chronological order (i.e. with the most recent formal educational qualification listed first). For each qualification, include:

• the commencing and end dates (month and year) for the qualification
• the full title of the qualification (e.g. Bachelor of Arts instead of B.A.)
• the institution attended and the enrolling school/administrative unit
• the city and country where the institution is located
• your Grade Point Average (GPA) for the overall qualification
• any academic achievement awards (e.g. Dean’s awards, subject prizes, University medals, thesis prizes etc.) received for the qualification
• if a research thesis was part of the qualification, include the title and word length of your dissertation.

As part of your application, please submit academic transcripts and degree certificates for each educational qualification you list.

Please do not include:

• high school qualifications
• the individual subjects/courses undertaken throughout your qualifications or the grades awarded for these
• training courses/professional development activities not resulting in a formal qualification.

Professional affiliations and memberships

List any professional/disciplinary associations or committees that you a member of and include:

• the commencing and end date (in years) for the affiliation/membership
• the name of the professional association or committee
• your membership type (e.g. student member, affiliate member, full member etc.) or role (e.g. committee member, secretary, president etc.).

Employment history

List each of your previous employment roles in reverse chronological order (i.e. with the most recent/current employment listed first) and include:

• the commencing and end dates (month and year) for the employment
• the title of each position
• the name of the employing organisation, the city, and country where you were based
• your main duties or accountabilities in that role, providing detailed information on any research-related activities
• any achievements during that role that are relevant to your proposed field of research .

Other research experience

List any voluntary, unpaid, or extra-curricular research-related projects or experiences you have undertaken (e.g. summer research projects, internships etc.) and include:

• the commencing and end dates (month and year) of the experience
• the name of the organisation, the city, and country where you were based

Research outputs

In reverse chronological order (i.e. the most recent output first) list your research outputs,  including for example research published or accepted for publication, research reports, and research by creative practice.

If needed, use sub-headings to separate refereed journal articles, published conference proceedings, edited book chapters, books, creative works, industry reports, invited papers, patents, media commentary, conference presentations and posters, invited talks etc. If applicable, use additional sub-headings to indicate if outputs are published , accepted for publication (but not yet in print), or (submitted but) under review .

Do not include any outputs/publications that are ‘in preparation’ .

For all research outputs, include:

• the output/publication reference using an official bibliographical style (such as Turabian/Chicago, APA, Harvard), including listing all authors in the order that they appear in the work with your name in bold
• the Digital Object Identifier (DOI), PubMed Identifier (PMID), International Standard Book Number (ISBN) or URL where applicable
• the standing of the journal or conference and the impact of the work (e.g. impact factors, citations and other metrics indicators)
• relevant indicators of national or international significance
• rejection rates for the outlet etc.
• how much of the original research you were responsible for (i.e. what was your role in the conception and design of the project and how involved were you in the analysis and interpretation of the research data on which the publication is based?)
• the extent to which you authored the paper.

Research grants and relevant awards

Include only those research grants and relevant awards that you have received at the time of making your application (i.e. do not list grants or awards that you applied for and did not receive or are awaiting a decision on). For each research grant/award, include:

• the name of the granting/awarding body and the country in which they are based
• the name of the grant/award
• the year(s) in which the grant was active or the year in which the award was made
• the amount of the research grant/award
• if relevant (e.g. for research grants), the title of your application.

Applicants from creative and professional-based disciplines may also include non-research grants and awards related to their creative or professional practice.

Research achievements relative to opportunity (optional)

In recognition of the diverse personal and professional pathways that applicants have experienced, you are invited to provide information ( maximum 200 words ) to contextualise your research outputs and achievements, relative to the opportunities that you have had to participate in research-related activities.

This section of the CV is optional and should only be included if you believe there are factors relevant to your research achievements that you would like the selection panels to know. Examples of factors include (but are not limited to):

• study/career disruptions due to illness, caregiving, natural disasters etc.
• non-linear academic or career progression, or a change in career direction
• reduced ability to take up research-related opportunities (e.g. attend conferences) due to caregiving responsibilities.

Academic referees

Please provide us with two referees who can comment on your academic work. For each referee, include their:

• honorific and name
• employing organisation and the city and country where they are located
• contact details, including office address, telephone, fax and email (preferably an institutional, rather than private, email address)
• an indication of the capacity in which you know this person (e.g. were they a lecturer or thesis supervisor, an employer, how long you’ve known them etc.). 

If possible, please include at least one:

• senior person (preferably your supervisor or the head of your organisational unit) closely associated with your current work, and
• person who is not a member of your proposed advisory panel/supervisory team.

Formatting and document specifications

We recommend that you use the below formatting settings to improve the readability of your CV:

• margins of at least 1.5 centimetres
• single line spacing
• no smaller than 12 point Times New Roman font (or equivalent)
• left justify text (not full justify)
• include your name and page number on each page
• be consistent in your formatting and spelling throughout
• limit the use of bold, underline, italics, and multiple font types.

Please proofread your CV carefully before uploading it to your application.

Save as a PDF and name your file: LASTNAME_firstname_CV.pdf

There is no page limit to your academic CV – it can be as long as required to include the information requested here.

Please include in your CV all the headings listed above – if you do not have any content to add for a particular heading please list ‘None to date’ under that heading .

An academic CV for employment purposes within Australia would not include the information requested here outlining your three most significant publications or your research achievements relative to opportunity. It would, however, include information about professional and service activities undertaken and may include a summary of your relevant research/teaching interest areas and skill sets – this information is not required in the CV you submit here for application to an HDR program.

This should show all study you have undertaken since secondary school, whether complete or incomplete, including the institution grading scale. The grading scale is often found on the final page or the reverse page; be sure to include all pages.

An academic transcript can also be called an:

• academic record
• diploma supplement
• statement of learning
• record of achievement.

A degree certificate is a legal document, imprinted with a university seal. It should state the name of your qualification and areas of study.

Include all degree certificates (testamurs) for post-secondary study with your application. If you studied in China, you must provide a:

• award certificate and
• graduate statement/certificate.

All applicants have to prove they can meet English language requirements . Any test scores have to be valid at your proposed commencement date.

Include a copy of the information page (with your photo) in your passport. This will verify your identity and ensure we can make offers correctly.

Include the contact details of two referees who will support your application. These referees will need to provide insight into your research experience.

We will contact your referees for a report, but you will need to enter their details into the application form.

Other documentation, originals or certified copies, may be required depending on your individual circumstances, for example:

• evidence of change of name
• proof of citizenship, if you are not a citizen of Australia or New Zealand by birth
• evidence of your Aboriginal and/or Torres Strait Islander status
• previous research program information .

If you don't provide us with all documents it will take us longer to process your application. Your start date might then be delayed, or you might miss an admission or scholarship deadline. 

4. Apply online

Once you have prepared your application and contacted a potential supervisor, use the online application form to apply. Your application can only be assessed once your referees have responded to us, and all outstanding documents and school/institute endorsements have been received.

Important dates

The academic year for research students is divided into four research quarters (RQ).

Candidates applying for a Student Visa or UQ scholarship may need to apply earlier. Make sure you check  scholarship round application deadlines  and outcome dates before applying.

The agreed start date will be included on your Confirmation of Enrolment.

Find out more about research quarter dates

The academic year for research students is divided into four research quarters (RQ). You can start a PhD in any quarter, as long as the Census Date hasn't passed.

Candidates applying for a UQ scholarship may need to apply earlier. Make sure you check scholarship round application deadlines and outcome dates before applying.

The agreed start date will be included on your offer of admission.

Aboriginal and Torres Strait Islander applicants

For support with applying – or if you have any questions about university life – get in touch with our Aboriginal and Torres Strait Islander Studies Unit.

Contact the ATSIS Unit

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School of Computer Science

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The degree is a four-year degree with an honours component, and it contains the sort of foundations and fundamentals required to get students started in the computing area – things like coding, programming and everything from databases and other type areas.

But the really exciting part is the fact that there is an opportunity for students to take different majors, such as internetworking applications, enterprise systems development, and areas where there’s a really huge need for their skills.

Computing science is an area that really demands technical skills, and those are the skills that are required in the future of our industries, and the future of innovation in Australia and also around the world.

It basically provides the foundation for things such as programming, coding, understanding the future of artificial intelligence research, data science. These are areas that really need technical skills – it needs people to be able to understand where they can learn the ability to actually get a computer to do very sophisticated processes, and this computing sciences area is actually exactly where they can get those skills, and where they can get the foundations for being relevant to industry and research. The types of students that we relish in undertaking a course like the Bachelor of Computing Science would be those that have a tremendous fundamental already within maths and a love for mathematics and computing in general, such as in the areas of coding and programming.

We’re looking for students who have a high technical ability, who love problem-solving and who can undertake the really big problems and challenges that the digital era faces in areas such as artificial intelligence, social robotics and quantum computing. In technology departments, or in technology-based organisations, we actually are increasingly embracing students that come from a very, very diverse set of degrees, because that diversity brings strength to our areas, and also reflects the great variety of work that we’ve got.

And then the counter to that is actually students coming through from computing science can go in so many different places, so computing science and technology is not the domain or the exclusive domain of technology groups anymore – it’s embedding right through organisations, and so I think a degree that gives you those technical skills combined with the ability to learn and adapt and grow over time, you can take that starting point anywhere these days I think.

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UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.

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Potential PhD projects

There are opportunities for talented researchers to join the School of Computer Science and Engineering, with projects in the following areas:

• Artificial Intelligence
• Biomedical Image Computing
• Data and knowledge research group

Embedded systems

• Networked systems
• Programming Languages & Compilers
• Service Orientated Computing
• Trustworthy Systems
• Theoretical Computer Science.

Artificial intelligence

Supervisory team : Professor Claude Sammut 

Project summary : Our rescue robot has sensors that can create 3D representations of its surroundings. In a rescue, it's helpful for the incident commander to have a graphical visualisation of the data so that they can reconstruct the disaster site. The School of Computer Science and Engineering and the Centre for Health Informatics have a display facility (VISLAB) that permits users to visualise data in three dimensions using stereo projection onto a large 'wedge' screen. 

This project can be approached in two stages. In the first stage, the data from the robot are collected off-line and programs are written to create a 3D reconstruction of the robot's surroundings to be viewed in the visualisation laboratory. In the second stage, we have the robot transmit its sensor data to the VISLAB computers for display in real-time. 

This project requires a good knowledge of computer graphics and will also require the student to learn about sensors such as stereo cameras, laser range finders and other 3D imaging devices. Some knowledge of networking and compression techniques will be useful for the second stage of the project. 

A scholarship/stipend may be available. 

For more information contact:  Prof. Claude Sammut

Supervisory team : Dr Raymond Louie

Project summary : Accurately predicting disease outcomes can have a significant impact on patient care, leading to early detection, personalized treatment plans, and improved clinical outcomes. Machine learning algorithms provide a powerful tool to achieve this goal by identifying novel biomarkers and drug targets for various diseases. By integrating machine learning algorithms with biological data, you will have the opportunity to push the boundaries of precision medicine and contribute to algorithms that can revolutionize the field.

We are looking for a highly motivated student who is passionate about applying computational skills to solve important health problems. Don’t worry, no specific biological knowledge is necessary, the important thing is you are enthusiastic and willing to learn. Please get in touch if you have any questions. 

For more information contact:  Dr. Raymond Louie

Supervisory team: Dr. Aditya Joshi

Project Summary: Discrimination and bias towards protected attributes have legal, social, and commercial implications for individuals and businesses. The project aims to improve the state-of-the-art in the detection of discrimination and bias in text. The project will involve creation of datasets, and development of new approaches using natural language processing models like Transformers. The datasets may include different text forms such as news articles, job advertisements, emails, or social media posts. Similarly, the proposed approaches may use techniques such as chain-of-thought prompting or instruction fine-tuning.

A scholarship/stipend may be available.

For more information, contact [email protected] .

Biomedical image computing

Supervisory team:  Dr Yang Song

Project summary:  Various types of microscopy images are widely used in biological research to aid our understanding of human biology. Cellular and molecular morphologies give lots of information about the underlying biological processes. The ability to identify and describe the morphological information quantitative, objectively and efficiently is critical. In this PhD project, we'll investigate various computer vision, machine learning (especially deep learning) and statistical analysis methodologies to develop automated morphology analysis methods for microscopy images.

More research topics in computer vision and biomedical imaging can be found  here .

For more information contact:  Dr Yang Song

Supervisor team:  Professor Erik Meijering and Dr John Lock

Project summary:  Biologists use multiparametric microscopy to study the effects of drugs on human cells. This generates multichannel image data sets that are too voluminous for humans to analyse by eye and require computer vision methods to automate the data interpretation. The goal of this PhD project is to develop, implement, and test advanced computer vision and deep learning methods for this purpose to help accelerate the challenging process of drug discovery for new cancer therapies. This project is in collaboration with the School of Medical Sciences (SoMS) and will utilise a new and world-leading cell image data set capturing the effects of 114,400 novel drugs on the biological responses (phenotypes) of >25 million single cells.

For more information contact:  [email protected] ,  [email protected]

Supervisor team:  Professor Erik Meijering and Professor Arcot Sowmya

Project summary:  Current commercial 3D ultrasound systems for medical imaging studies often do not provide the ability to record volumes large enough to visualise entire organs. The first goal of this PhD project is to develop novel computational methods for fast and accurate image registration to digitally reconstruct whole organs from multiple ultrasound volumes. The second goal is to develop computer vision and deep learning methods for automated volumetric image segmentation and downstream statistical analysis. This project will be in collaboration with researchers from the UNSW School of Women’s and Children’s Health to improve monitoring organ development during pregnancy to support clinical diagnostics.

For more information contact:  [email protected] ,  [email protected]

Supervisor team:  Prof. Arcot Sowmya, A/Prof. Lois Holloway (Ingham Medical Research Institute, Liverpool Hospital)

Project summary:  Decisions on the most appropriate treatment for diseases such as colorectal cancer and diverticulitis can be complex. Advanced imaging such as MRI and CT can provide information on the location of the disease compared to other anatomy and also functional information on the disease and surrounding organs. There is also the potential to gain additional information from these images using techniques such as radiomics. At Liverpool hospital, there is a database of previous patient histories, including outcome as well as imaging information which we can use in collaboration with medical specialists. This project will use machine learning and deep learning approaches to determine anatomical and disease boundaries and combine them with clinical and response data to model treatment response and develop treatment decision support tools. The incoming PhD student should ideally have a computer science qualification with research skills and an interest to develop deep learning and decision support techniques in the medical imaging field. Research in this area is subject to ethics approvals and institutional agreements.

For more information contact:  [email protected] ,  [email protected]

Supervisor team:  Prof. Arcot Sowmya and Dr Simone Reppermund

Depression and self-harm represent substantial public health burdens in the older population. Depression is ranked by the WHO as the single largest contributor to global disability and is a major contributor to suicide. This project will use large linked administrative health datasets to examine health profiles, service use patterns and risk factors for suicide in older people with depression. Given the vast amount of data included in linked datasets, new ways of analysing the data are necessary to capture all relevant data signals. This project will generate a sound epidemiological and service evidence base that informs our understanding of health profiles and service system pathways in older people with depression and risk factors for trajectories into suicide.

For more information contact:  [email protected] ,  [email protected]

Data & knowledge research group

Supervisory team:  Xuemin Lin, Wenjie Zhang 

Project summary:  Efficient processing of large scale multi-dimensional graphs.

This project aims to develop novel approaches to process large scale graphs such as social networks, road networks, financial networks, protein interaction networks, etc. The project will focus on the three most representative types of problems against graphs, namely cohesive subgraph computation, frequent subgraph mining and subgraph matching. The applications include anomaly detection, community search, fraud and crime detection.  

For more information contact:  [email protected]  or  [email protected]   

Supervisory team:  Wei Wang, Xin Cao 

Project summary:  The immense popularity of online social networks has resulted in a rich source of data useful for a wide range of applications such as marketing, advertisement, law enforcement, health and national security, to name a few. Ability to effectively and efficiently search required information from huge amounts of social network data is crucial for such applications. However, current search technology suffers from several limitations such as inability to provide geographically relevant results, inadequately handling uncertainty in data and failing to understand the data and queries, resulting in inferior search experience. This project aims to develop a next-generation search system for social network data by addressing all these issues. 

For more information contact:  [email protected]  or  [email protected]   

Supervisory team:  Sri Parameswaran 

Project summary:  Reliability is becoming an essential part in embedded processor design due to the fact that they are used in safety critical applications and they need to deal with sensitive information. The first phase in the design of reliable embedded systems involves the identification of faults that could be manipulated into a reliability problem. A technique that is widely used for this identification process is called fault injection and analysis. The aim of this project is to develop a fault injection and detection engine at the hardware level for an embedded processor. 

For more information contact:  [email protected]

Human-Centred Computing

Supervisory team:   Dr. Gelareh Mohammadi , Prof. Sowmya Arcot

Project summary:  We’ve seen stunning results from modern RL in arenas such as playing games, where the environment is constrained, predictable and it is possible to simulate a huge number of experiences. Major limiting factors are that current technology is not able to learn from a few experiences (few-shot learning), and to learn new tasks without forgetting old ones (continual learning). Neither has been well addressed and are usually investigated separately. In stark contrast, they are trivial for animals, and common in even simple real world scenarios. To advance the state-of-the-art continual and few-shot RL within a single architecture. The project is inspired by evidence that in our brains, the Hippocampus constitutes a short term memory and it replays to the frontal cortex directly. It is likely used for world-model building, as opposed to the mainstream view in cognitive science and ML - where 'experience replay' ultimately improves policy.

Supervisory team: Dr Gelareh Mohammadi ,  Prof. Wenjie Zhang

Project description: Previous studies have shown that cognitive training can effectively improve people's skillsets and emotional capabilities in cognitive deficits. Such training programs are known to enhance the participants' brain health and better prepare them for an independent life. However, the existing conventional technologies for such training are not scalable and lack personalized features to optimize the efficacy. In this project, we will develop a technology platform for automatically acquiring and processing multimodal training data. The project will be conducted in collaboration with Stronger Brains, a not-for-profit organization that provides cognitive training. We aim to develop a fully automated social and cognitive function assessment framework based on multimodal data. Such a framework is essential to establish a  system with less involvement of experts and increase its scalability. The project involves:

• Data collection.
• Developing multimodal predictive models for cognitive functions and affective states in cognitive deficits.
• Developing adaptation techniques to personalize the framework.

Supervisory team: Dr Gelareh Mohammadi , A/Prof. Nadine Marcus

Project description: The fields of Science, Technology, Engineering and Math, otherwise known as STEM, play a key role in the sustained growth and stability of any economy and are a critical component in shaping the future of our society. This project aims to develop new evidence-based guidelines for designing highly effective teaching simulations for a STEM subject that personalizes training to learner proficiency. In particular, we aim to design a novel AI-powered framework for dynamic adaptive learning in STEM educational technology to improve learning outcomes in an accessible and engaging environment. The potential contributions of the project involve:

• Developing a multimodal physio-behavioural AI for rapid assessment of proficiency level.
• Integration of affective state and cognitive load with proficiency level to form a comprehensive cognitive diagnosis and capture the interplay between affective and cognitive processes.
• Establishing dynamic adaptive learning in real-time based on the cognitive diagnosis that responds to the current individual needs of the learner.

Networked systems and security

Supervisory team:  Sanjay Jha, Salil Kanhere 

Project summary:  This project aims to develop scalable and efficient one-to-many communication, that is, broadcast and multicast, algorithms in the next generation of WMNs that have multi-rate multi-channel nodes. This is a significant leap compared with the current state of the art of routing in WMNs, which is characterised by unicast in a single-rate single-channel environment. 

For more information contact:  [email protected]

Supervisory team:  Mahbub Hanssan 

Project summary:  A major focuses of the Swimnet project will be to look at a QoS framework for multi-radio multi-channel wireless mesh networks. We also plan to develop traffic engineering methodologies for multi-radio multi-channel wireless mesh networks. Guarding against malicious users is of paramount significance in WMN. Some of the major threats include greedy behaviour exploiting the vulnerabilities of the MAC layer, location-based attacks and lack of cooperation between the nodes. The project plans to look at a number of such security concerns and design efficient protection mechanisms (Mesh Security Architecture). 

For more information contact:  [email protected]   

Supervisory team:  Wen Hu  

Project summary:  The mission of the SENSAR (Sensor Applications Research) group is to investigate the systems and networking challenges in realising sensor network applications. Wireless sensor networks are one of the first real-world examples of "pervasive computing", the notion that small, smart and cheap, sensing and computing devices will eventually permeate the environment. Though the technologies still in their early days, the range of potential applications is vast - track bush fires, microclimates and pests in vineyards, monitor the nesting habits of rare sea-birds, and control heating and ventilation systems, let businesses monitor and control their workspaces, etc. 

For more information contact:  [email protected]

Service orientated computing

Supervisory team:  Boualem Benatallah, Lina Yao, Fabio Casati

Project summary:  This project investigates the significant and challenging issues that underpin the effective integration of software-enabled services with cognitive and conversational interfaces. Our work builds upon advances in natural language processing, conversational AI and services composition.

We aim to advance the fundamental understanding of cognitive services engineering by developing new abstractions and techniques. We’re seeking to enable and semi-automate the augmentation of software and human services with crowdsourcing and generative model training methods, latent knowledge and interaction models. These models are essential for the mapping of potentially ambiguous natural language interactions between users and semi-structured artefacts (for example, emails, PDF files), structured information (for example, indexed data sets), apps and APIs.

For more information contact:  [email protected]  or  [email protected]

Supervisory team:  Lina Yao and Defence Science & Technology Group

Project summary:  This research is supported by the Defence Science and Technology Group. It aims to develop intelligent methodologies to capture the environment in sufficient fidelity to evaluate (model and predict) what application/system changes need to occur to fulfil the requirements (goals) of the mission.

For more information contact:  [email protected]

Supervisory team:  Lina Yao, Boualem Benatallah and Quan Z. Sheng

Project summary:  The overall goal of this project is to develop novel machine learning and deep learning techniques that can accurately monitor and analyse human activities. These techniques will monitor and analyse daily living on a real-time basis and provide users with relevant, personalised recommendations, improving their lifestyle through relevant recommendations.

For more information contact:  [email protected]  or  [email protected]

Supervisory team:  Lina Yao

Project summary : This project is supported by Office of Naval Research Global (US Department of Navy). The aim of this project is to develop a software package for resilient context-aware human intent prediction for human-machine cooperation.

Supervisory team:  Lina Yao and Xiwei Xu

Project summary:  The research is supported by our collaborative research project with Data61. The aim is to develop an integrated end-to-end framework for fostering trust in Federated/Distributed AI systems.

For more information contact:  [email protected]  or  [email protected]

Supervisory team:  Helen Paik

Project summary:  Micro-transactions stored in blockchain create transparent and traceable data and events, providing burgeoning industry disruptors an instrument for trust-less collaborations. However, the blockchain data and its’ models are highly diverse. To fully utilise its potential, a new technique to efficiently retrieve and analyse the data at scale is necessary.

This project addresses a significant gap in current research, producing a new data-oriented system architecture and data analytics framework optimised for online/offline data analysis across blockchain and associated systems. The outcome will strongly underpin blockchain data analytics at scale, fostering wider and effective adoption of blockchain applications. A scholarship/stipend may be available.

For more information contact:  [email protected]

Supervisory team:  Fethi Rabhi and Boualem Benatallah

Project summary:  All modern organisations use some form of analytics tools. Configuring, using and maintaining these tools can be very costly for an organisation. Analytics tools require expertise from a range of specialties, including business insight, state-of-the-art modelling approaches and tools such as AI and machine learning as well as efficient data management practices. A knowledge engineering approach can deliver flexible and custom data analytics applications that align with organisational objectives and existing IT infrastructures. This model uses existing resources and knowledge within the organisation. The project uses semantic-web based knowledge modelling techniques to build a comprehensive view related to an organisation’s analytics objectives while leveraging open knowledge and open data to expand its scope and reduce costs.

We aim to help organisations utilise and reuse public and organisational knowledge efficiently when conducting data analytics. Our work also involves the rapid development and deployment of analytics applications that suit emerging analytics needs, plugging new data and software on-demand using new approaches such as APIs and cloud services. The proposed techniques have already been piloted in the areas of house price prediction in collaboration with the NSW Government and portfolio management in collaboration with Ignition Wealth.

For more information contact:  [email protected]  or  [email protected]

Theoretical computer science

Supervisory team:  Ron van der Meyden 

Project summary:  The technology of cryptocurrency and its concepts can be broadly applicable to range of applications including financial services, legal automation, health informatics and international trade. These underlying ideas and the emerging infrastructure for these applications is known as ‘Distributed Ledger Technology’. 

For more information contact:  [email protected]   

Trustworthy systems

Supervisory team:  Gernot Heiser, June Andronick 

Project summary:  seL4, the secure embedded L4 microkernel, is a key element of our research program. We developed seL4 to provide a reliable, secure, fast and verified foundation for building trustworthy systems. seL4 enforces security within componentised system architectures by ensuring isolation between trusted and untrusted system components and by carefully controlling software access to hardware devices in the system. 

For more information contact:  [email protected]  or  [email protected]

Supervisory team: Dr Arash Shaghaghi, Prof Sanjay Jha, Dr Raymond K. Zhao, Dr Nazatul Sultan

Project summary : A PhD scholarship is available for applicants with outstanding research potential and an interest in quantum-safe security measures for IoT deployments. The successful applicant will join a group of researchers from the School of Computer Science and Engineering (CSE) of UNSW Sydney, the UNSW Institute for Cyber Security (IFCYBER), and CSIRO. The research team brings a complementary track record and expertise aimed to tackle a project of significant potential for impact addressing an emerging topic of research.

We particularly encourage applications from those interested in practical system research (i.e., applied cryptography), noting that our goal is to enhance the resiliency of IoT deployments within intelligent transportation against quantum-based attacks. The project will develop a systematic approach and devise a testbed for evaluating quantum-based attacks against IoT deployments in critical infrastructure. The project’s findings will inform quantum-safe migrations in intelligent transport systems in Australia and internationally.

For more information contact: [email protected] or [email protected]

Projects with top up scholarship for domestic students

Supervisors:

• Dr Gelareh Mohammadi ( [email protected] )
• Prof. Wenjie Zhang ( [email protected] )

Project description:

Previous studies have shown that cognitive training can effectively improve people's skillsets and emotional capabilities in cognitive deficits. Such training programs are known to enhance the participants' brain health and better prepare them for an independent life. However, the existing conventional technologies for such training are not scalable and lack personalized features to optimize the efficacy. In this project, we will develop a technology platform for automatically acquiring and processing multimodal training data. The project will be conducted in collaboration with Stronger Brains, a not-for-profit organization that provides cognitive training. We aim to develop a fully automated social and cognitive function assessment framework based on multimodal data. Such a framework is essential to establish a  system with less involvement of experts and increase its scalability. The project involves:

• A/Prof. Nadine Marcus  ([email protected] )

The fields of Science, Technology, Engineering and Math, otherwise known as STEM, play a key role in the sustained growth and stability of any economy and are a critical component in shaping the future of our society. This project aims to develop new evidence-based guidelines for designing highly effective teaching simulations for a STEM subject that personalizes training to learner proficiency. In particular, we aim to design a novel AI-powered framework for dynamic adaptive learning in STEM educational technology to improve learning outcomes in an accessible and engaging environment. The potential contributions of the project involve:

Supervisor:  Dr Rahat Masood ( [email protected] )

Supervisory team:  Prof Salil Kanhere (CSE - UNSW), Suranga Seneviratne (USyd), Prof Aruna Seneviratne (EE&T – UNSW)

Children start using the Internet from a very early age for entertainment and educational purposes and continue to do so into their teen years and beyond. In addition to providing the required functionality, the online services also collect information about their users, track them, and provide content that may be inappropriate such as sexually explicit content; content that promotes hate and violence, and other content compromising users’ safety. Another major issue is that there is no established mechanism to detect the age of users on online platforms hence, leading children to sign up for services that are inappropriate for them. Through this research work, we aim to develop an age detection framework that can help detect children’s activities on online platforms using various behavioural biometrics such as swipes, keystrokes, and handwriting. The core of this project revolves around the ground-breaking idea that “User Touch Gestures” contain sufficient information to uniquely identify them, and the “Touch Behaviour” of a child is very different from that of an adult, hence leading to child detection on online platforms. The success of this project will enable online service providers to detect the presence of children on their platforms and offer age-appropriate content accordingly.

• Dr Rahat Masood ( [email protected] )
• Prof. Salil Kanhere (CSE - UNSW)

Users unintentionally leave digital traces of their personal information, interests and intents while using online services, revealing sensitive information about them to online service providers. Though, some online services offer configurable privacy controls that limit access to user data. However, not all users are aware of these settings and those who know might misconfigure these controls due to the complexity or lack of clear instructions. The lack of privacy awareness combined with privacy breaches on the web leads to distrust among the users in online services. Through this research study, we intend to improve the trust of users on the web and mobile services by designing and developing user-centric privacy-preserving solutions that involve aspects of user privacy settings, user reactions and feedbacks on privacy alerts, user behavioural actions and user psychology. The aforementioned factors will be first used in quantifying privacy risks and later used in designing privacy-preserving solutions. In essence, we aim to improve privacy in mobile and web platforms by investigating various human factors in: i) privacy risk quantification and assessment, and ii) privacy-preserving solutions.

• Dr Yang Song ( [email protected] ) - primary
• Prof. Maurice Pagnucco - joint

Deep learning techniques have shown great success in many applications, such as computer vision and natural language processing. However, in many cases, purely data-driven approaches would provide suboptimal results, especially when limited data are available for training the models. This dependency on large-scale training data is well understood as the main limitation of deep learning models. One way to mitigate this problem is to incorporate knowledge priors into the model, similarly to how humans reason with data; and there are various types of knowledge priors, such as data-specific relational information, knowledge graphs, logic rules and statistical modelling. In this PhD project, we will investigate novel methods that effectively integrate knowledge priors and commonsense reasoning with deep learning models. Such models can be developed for a wide range of application domains, such as computer vision, social networks, biological discovery and human-robot interaction.

Deep learning models are typically considered a black-box, and the lack of explainability has become a major obstacle to deploy deep learning models to critical applications such as medicine and finance. Explainable AI has thus become an important topic in research and industry, especially in the deep learning era. Various methods for explaining deep learning models have been developed, and we are especially interested in explainability in graph neural networks, which is a new topic that has emerged very recently. Graph neural networks are becoming increasingly popular due to their inherent capability of representing graph structured data, yet their explainability is more challenging to explore with the irregular and dynamic nature of graphs. In this PhD project, we will investigate novel ways of modelling explainability in graph neural networks, and apply this to various applications, such as computer vision, biological studies, recommender systems and social network analysis.

• Dr Dong Wen ( [email protected] ) - primary
• Prof. Wenjie Zhang ( [email protected] ) 

Due to the graph’s strong expressive power, a host of researchers are turning to graph modelling to support real-world data analysis. Given the prevalence of graph structures with temporal information in user activities, temporal and dynamic graph processing is an important and growing field of computer science. Driven by a wide spectrum of applications, such as recommendation and fraud detection in e-commerce, and malicious software detection in cybersecurity, this project aims to develop novel techniques for scalable and efficient temporal graph processing. The specific focus is to tame the challenges brought by the large volume, the high velocity, the complex structure of big temporal and dynamic graphs. The project will lay theoretical foundations and deliver substantial outcomes including computing frameworks, novel indexes and incremental and approximate algorithms to process large-scale graphs.

Supervision team

•  Dr Jiaojiao Jiao ( [email protected] ) – primary
•  Prof. Sanjay Jha ( [email protected] ) – joint
•  Stephen Doherty ( [email protected] ) - secondary

Most cyber threat intelligence platforms provide scores and metrics that are mainly derived from open-source and external sources. Organisations must then figure out if and how the output is relevant to them.

Research problems

• Dynamic threat risk/exposure score

Continuous monitoring and calculation of an organisation’s ‘Threat Risk’ posture score using a range of internal and external intelligence.

• Customised/targeted newsfeed

A curated cyber and threat newsfeed that is relevant to an organisation. The source of the newsfeed will leverage the internal and external analysis from the first question. The output will include information that helps users understand and digest their organisation’s threat posture in a non-technical manner.

Proposed approaches

We propose to develop dynamic GNN models for discovering dynamic cyber threat intelligence from blended sources. GNN has achieved state-of-the-art performance in many high-impact applications, such as fraud detection, information retrieval, and recommender systems, due to their powerful representation learning capabilities. We propose to develop new GNN models which can take blended intelligence sources into account in the threat intelligence prediction. Moreover, many GNN models are static that deal with fixed structures and parameters. Therefore, we propose to develop dynamic GNN models which can learn the evolution pattern or persistent pattern of dynamic graphs.

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Bachelor's Degree in Computer Science

Why pursue a bachelor's degree in computer science.

The concentration in Computer Science is designed to teach students skills and ideas they will use immediately and in the future. Because information technology affects every aspect of society, graduates with computer science degrees have open to them an enormous variety of careers—engineering, teaching, medicine, law, basic science, entertainment, management, and countless others. 

At Harvard College, students choose a "concentration," which is what we call a major. All prospective undergraduate students, including those intending to study engineering and applied sciences, apply directly to Harvard College . During your sophomore spring you’ll declare a concentration, or field of study. You may choose from 50 concentrations and 49 secondary field (from Harvard DSO website ).

All undergraduates in Computer Science at Harvard are candidates for the Bachelor of Arts degree (A.B.) . With the knowledge that it requires extra course work, you can consider the more intensive  A.B./S.M. option  through a concurrent masters degree.

Learn about our Computer Science concentrators  >

Apply to Harvard College  >

A.B. in Computer Science

The basic degree requirements are eleven to fourteen 4-credit courses in mathematics, theoretical computer science, computer software, and other areas of computer science. Math courses cover linear algebra, single variable calculus and probability/statistics. Students who place out of part or all of the introductory calculus sequence, Mathematics 1ab, reduce their concentration requirements to 11 courses.

Computer Science Secondary Field

A lightweight way of getting official recognition within Harvard for work in two fields is to do one or the other as a secondary field. For Computer Science, this involves taking 4 courses in the secondary field. Learn more about the  computer science secondary field .

A.B./S.M. in Computer Science

Our  AB/SM degree program  is for currently enrolled Harvard College students only. Students who are eligible for  Advanced Standing  on the basis of A.P. tests before entering Harvard may be able to apply for admission to the S.M. program of the Graduate School of Arts and Sciences and graduate in four years with both a bachelor’s and master’s degree (not necessarily in the same field).

Beginning with the class of 2022, students have the opportunity to apply to the Graduate School of Arts and Sciences for a master’s degree pursued concurrently with the bachelor’s degree. As part of the  concurrent degree program , students will be allowed to double-count up to sixteen credits (normally, four courses) for the Bachelor of Arts and the Master of Science. An undergraduate pursuing the concurrent degree must complete both of these degrees by the end of eight terms of residency, or the equivalent.

The Mind, Brain, and Behavior Program (MBB)

Students interested in addressing questions of neuroscience and cognition from the perspective of computer science may pursue a special program of study affiliated with the University-wide Mind, Brain, and Behavior Initiative, that allows them to participate in a variety of related activities. (Similar programs are available through the Anthropology, History and Science, Human Evolutionary Biology, Linguistics, Neurobiology, Philosophy, and Psychology concentrations.) Requirements for this honors-only program are based on those of the computer science Requirements for Honors Eligibility. See the  handbook entry  for more information and also  Frequently Asked Questions about the MBB Track . This is an honors track program: students are eligible for English Honors.

Why study CS at Harvard? What’s different about pursuing CS in a liberal arts setting?

Get the answer to these questions and learn more about CS .

Prerequisites

Learn about the prerequisites for the concentration on our  First-Year Exploration page . Students interested in concentrating in computer science can refer to our Sophomore Advising page  and request to be matched with a Peer Concentration Advisor  (PCA). PCAs serve as peer advisors for pre-concentrators (and current concentrators), providing a valuable perspective and helping students to discover additional resources and opportunities.

Requirements

Learn more about the Computer Science requirements >

View current Computer Science courses . >

View sample plans of study. >

Tags for Computer Science courses. > 

Research Opportunities in Computer Science

As part of your Bio/Biomedical Engineering coursework, or perhaps as part of individual research opportunities working with professors, you will have the chance to take part in or participate in some extraordinary projects.  Learn more about research opportunities at Harvard SEA S.

Learn about the research interests of our Computer Science faculty .

Computer Science Career Paths

Learn about potential career paths for students for students concentrating in Computer Science . 

Computer Science & Society

Harvard Computer Science has several programs that allow undergraduate students to think about the broader issues in tech and CS.

Computer Science Clubs and Organizations

SEAS-affiliated student organizations are critical to the overall growth of our concentrators as engineering and applied science professionals. These organizations enable our students to pursue passion projects and events in areas of interest that are complementary to the current formal academic curriculum. Learn more about computer science student clubs and organizations .

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