PhD Studentship : Research Studentship in High Performance AI Systems

3.5-year D.Phil. studentship 

Project: Scaling AI Systems

Supervisors: Prof Noa Zilberman, Prof Amro Awad

You will join a revolutionary new project, rethinking the way we build AI training systems.  You will work together with 15 researchers from different disciplines, and learn from the world leading academics working on the project: Prof Amro Awad, Prof Martin Booth, Prof Nick McKeown, Prof Dominic O’Brien, Dr Patrick Salter and Prof Noa Zilberman.

The project aims to solve the existing bottlenecks in AI training, and introduce a new interconnect for it. The project rethinks system design at multiple levels, from the low-level physical design to the highest-level application. It combines innovation in photonics, networking, computer architecture, memory systems, hardware/software co-design, distributed systems and more. It will address real-world challenges such as resilience and recovery, manufacturability, and operational constraints.

You will research a novel AI systems design, covering aspects of distributed systems, hardware/software co-design, resilience and recovery, and sustainability. 

Eligibility

This studentship is funded by ARIA through the Scaling AI Systems project and is open to Home or/and overseas students (full award –fees plus stipend).

Award Value

Course fees are covered at the level set for overseas students c. £33,370 p.a. The stipend (tax-free maintenance grant) is c. £19,237 p.a. for the first year, and at least this amount for a further two and a half years. 

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

• A first class honours degree in Engineering or Computer Science
• Excellent English written and spoken communication skills
• Excellent knowledge in distributed systems
• Excellent programming skills (C/C++ and scripting languages)

The following skills are desirable but not essential:

• A distinction or first class honours Masters degree in Engineering or Computer Science
• Previous research experience in the subject area (e.g., final year project, internship)
• Previous experience in distributed AI workloads
• Previous experience writing for publication

Application Procedure

Informal enquiries are encouraged and should be addressed to Prof Noa Zilberman (noa.zilberman@eng.ox.ac.uk).

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria.  Details are available on the course page of the University website.

Please quote 25ENGEL_NZ3 in all correspondence and in your graduate application.

Application deadline: noon on 3 December 2024 (In line with the University admissions deadline set by the University)

Start date: October 2025

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