[Full award covering course fees for Home or Overseas students plus UKRI minimum stipend (tax-free maintenance grant) for at least 2.5 years.] The University of Oxford is offering a 3.5-year D.Phil. studentship focused on 'Networking for Frontier AI' within the field of computer networks. This research opportunity, supervised by Professor Noa Zilberman, aims to address the evolving challenges in computer network design driven by the training and deployment of advanced AI models. The project centers on innovative networking solutions for frontier AI systems, with a particular emphasis on the architecture and role of network switches in achieving sub-1 nanosecond latency between accelerators. Candidates will investigate how operations are partitioned between switches and edge devices, and develop novel networking solutions to accelerate AI system performance. This studentship is funded by the VMware University Research Fund and is open to both Home and Overseas students. The award includes full coverage of course fees at the appropriate rate and a tax-free maintenance grant (UKRI minimum stipend) for at least two and a half years. The position is ideal for students with a strong background in Engineering or Computer Science, particularly those with expertise in computer networks, hardware design (Verilog), and programming (C/C++ and/or Python). Additional desirable skills include a distinction or first class honours Masters degree, research experience, FPGA or ASIC design, network simulation, and academic writing. Applicants must meet the University of Oxford's graduate admissions criteria and submit a graduate application form, quoting reference 26ENGIN_NZ. Informal enquiries are encouraged and can be directed to Professor Noa Zilberman at [email protected]. The application deadline is noon on 3 March 2026, with the successful candidate expected to start in October 2026. This studentship provides an excellent opportunity to contribute to cutting-edge research at the intersection of computer networks and artificial intelligence, within a world-leading academic environment.

This 3.5-year D.Phil. (PhD) studentship at the University of Oxford's Department of Engineering Science offers an exciting opportunity to research innovative networking solutions for frontier AI systems. The project, supervised by Professor Noa Zilberman, focuses on the architecture of network switches and their critical role in enabling sub-nanosecond latency between AI accelerators. You will investigate how operations are partitioned between switches and edge devices, and develop novel networking solutions to accelerate the performance of advanced AI systems. The studentship is fully funded through the VMware University Research Fund and is open to both Home and Overseas students. The award covers full course fees at the appropriate rate and provides a tax-free maintenance stipend at the UKRI minimum (or higher) for the duration of the project. The research will combine expertise in computer networks, hardware design (including Verilog), and programming (C/C++ and/or Python), with opportunities to gain experience in FPGA or ASIC design, network simulation, and academic publication. Applicants should have a first class or strong upper second-class undergraduate degree with honours (or equivalent) in Engineering or Computer Science. Excellent English communication skills, strong knowledge of computer networks, and proficiency in hardware and software design are essential. A distinction or first class honours Masters degree, prior research experience, and skills in FPGA/ASIC design or network simulation are desirable but not required. All candidates must meet the University of Oxford's graduate admissions criteria. Informal enquiries are encouraged and can be directed to Professor Noa Zilberman at [email protected]. To apply, submit a graduate application form via the University of Oxford website, quoting reference 26ENGIN_NZ, and ensure you meet all admissions requirements. The application deadline is noon on 3 March 2026, with the studentship commencing in October 2026. For further details and to access the application portal, please visit the official FindAPhD listing or the University of Oxford course page.