PhD Studentship in Machine-Learning Guided Compilation (Fixed Term)

Fixed-term: The funds for this post are available for 48 months.

The Project

Applications are invited for a PhD student to work on machine-learning guided and verifiably correct code generation.

Creating optimised libraries is a difficult and time-consuming task, requiring significant manual engineering effort. This process must be repeated for each new processor to take advantage of additional features, especially when it implements the latest architecture with new instructions or significant new architectural extensions, like Arm's SVE and SME. However, advances in machine learning point towards a low-cost solution to this task by automating code generation through a series of provably correct steps. A machine-learning model will guide the search for optimised code sequences, learning the best instructions to use for given intermediate code fragments and alleviating manual engineering effort.

The successful candidate will develop new code-generation strategies using machine-learning models and verification tools, suitable for deployment by library writers within the compilation toolchain, working closely with project partner, Arm.

Research Group

Our group consists of PostDocs and PhD students investigating performance, reliability and security in future many-core systems. We develop solutions within compilers, computer architectures and all associated tools, with a strong focus on parallelism. The position is within the Computer Architecture Research Group at the University of Cambridge Department of Computer Science and Technology, a vibrant and internationally leading environment. Collaboration with researchers at other universities and industry around the world is encouraged and there are strong links within the group with local, national and international companies.

Candidates

We seek candidates with a strong background in Computer Science (1st class honours degree or equivalent, although a Master's is particularly desirable) with a particular interest in compilers or binary modification tools and machine learning. Experience of writing code for a tool such as LLVM or DynamoRIO would be helpful, as would familiarity with working in teams with robust engineering practices (version control, continuous integration, automated testing)..

Non-UK applicants may apply but will be expected to arrange the balance between the home rate and overseas rate fees themselves. Note that this studentship does not include the immigration health surcharge or visa costs. https://www.ukri.org/our-work/developing-people-and-skills/find-studentships-and-doctoral-training/get-a-studentship-to-fund-your-doctorate/

Full details of the University's entrance requirements and scholarships are specified on the following link: https://www.postgraduate.study.cam.ac.uk/

Application Process

Please make your application through the University Application Portal: https://www.postgraduate.study.cam.ac.uk/courses/directory/cscspdpcs

Students wishing to pursue a PhD at the University of Cambridge are required to submit a short research proposal outlining the work they intend to carry out during the PhD. Candidates should get in touch with Prof. Timothy Jones, [email protected] to discuss this before applying, outlining their ideas for initial research directions.

More Information

The funds are available for a start date in October 2024 but there is some flexibility to enable a start at other points in the academic year.

Further details may be obtained from Prof. Timothy Jones, [email protected]

Your online application will need to include two academic references, an academic transcript, a CV and a developed research proposal of no more than 3,000 words in one of the general areas of research defined above. Please indicate the relevant Professor as a potential supervisor.

Also provide a covering letter outlining your relevant past experience, drawing particular attention to relevant software experience and linking to one or more examples of code written (e.g. a GitHub handle). If there were specific areas, you would like to research, please indicate these in the letter.

Please quote reference NR40808 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.