PhD Studentship in Computer Architecture and Compilers: Memory Optimisation for Distributed ML Systems University of Edinburgh in United Kingdom

This fully funded PhD studentship at the School of Informatics, University of Edinburgh, offers an exciting opportunity to work with Dr Jianyi Cheng on the project “Memory Optimisation for Distributed ML Systems.” The research aims to develop advanced techniques for automatically mapping emerging machine learning models onto efficient spatial systems, addressing key challenges in computer architecture and compilers for distributed environments.

The School of Informatics is renowned as one of the largest and most prestigious in Europe, consistently ranked among the world’s top institutions for research power and societal impact. The University of Edinburgh provides a vibrant, international academic environment with access to several centres of excellence and cutting-edge resources.

The studentship covers full-time PhD tuition fees for both Home (£6,300 per annum) and Overseas (£34,800 per annum) students, along with a tax-free stipend at the UKRI rate (£21,805 per year for 2026/27, with annual increases) for 3.5 years. Applications are welcome from candidates worldwide.

Applicants should have a strong motivation to learn and explore new technologies, with experience in accelerator system programming (such as CUDA or SGLang). A good Bachelor’s Honours degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject (physics, mathematics, engineering, computer science, or related field) is required. Proficiency in English (oral and written) is essential, and knowledge of compilers or ML systems is highly desirable.

To apply, candidates must submit all degree transcripts and certificates (with certified translations if applicable), evidence of English language capability (where required), a short research proposal (max 2 pages), a full CV and cover letter (max 2 pages), and two references or referee contact details. Only complete applications will be considered. The anticipated start date is 1 September 2026, with flexibility for later start dates if needed.

Applications should be submitted via the University’s admissions portal (EUCLID) for the PhD in ICSA programme. Applicants must specify “Memory Optimisation for Distributed ML Systems” as the research topic and Dr Jianyi Cheng as the proposed supervisor. The deadline for full consideration is 1 June 2026; applications received after this date will be considered until the position is filled.

For more information and to apply, visit the official programme page or the FindAPhD listing.