Oxford–UBS Centre for Applied AI DPhil Studentship: Future AI Systems for Finance

3.5-year DPhil studentship 

Fully funded doctoral studentships for October 2027 entry

Supervisors: Professor Noa Zilberman, Engineering Science, in collaboration with the Oxford–UBS Centre for Applied AI at Saïd Business School

The Oxford–UBS Centre for Applied AI is a joint initiative between Saïd Business School and Oxford’s Mathematical, Physical and Life Sciences Division, focusing on collaboration with Computer Science and Engineering.

The Centre invites applications from outstanding prospective DPhil candidates interested in the development, adoption and impact of AI in business, finance and society. The successful candidate will join its multidisciplinary research community, working at the interface of engineering, computer science, finance and management.

Future AI Systems for Finance explores how next-generation AI systems can be designed, deployed and maintained for the specific needs of financial organisations. The project addresses current limitations in AI inference systems, particularly where enterprise and finance applications require efficient, resilient and adaptable compute infrastructure. It will investigate areas such as novel accelerator architectures, hardware-software co-design, AI service orchestration across the compute continuum, and infrastructure that can evolve with changing AI requirements.

Research Focus

Today, most AI systems research is focused either on large scale systems deployed by hyperscalers, or small-scale solutions deployed on end-user devices. Little attention is paid to systems that are tailored for enterprises, or specifically to banks and finance. The goal of this project will be to develop new AI systems that have applications in finance as a core objective. With new AI models, novel accelerators and new deployment scenarios emerging, this may cover:

• Efficient orchestration and deployment of AI services across the (finance) compute continuum

• Use of novel AI accelerators and systems for finance

• Hardware-software co-design for AI in finance

• Rapid evolution of compute infrastructure in the presence of evolving AI needs

• Resilient AI compute infrastructure for finance

The project is highly interdisciplinary and the successful candidate will have the opportunity to collaborate with other members of the Centre and the Department.

Eligibility

These studentships are funded by the Oxford–UBS Centre for Applied AI, sponsored by UBS AG.

The studentship covers tuition fees and an annual stipend of at least £21,805, in line with the UKRI rate, for 3.5 years (42 months). One award is available to a Home student and one to an Overseas student. Applicants are encouraged to pursue other University, college or external co-funding opportunities.

Award Value

Course fees are covered for Home and overseas students. The stipend (tax-free maintenance grant) is c. £ 21,805 p.a. for the first year, and at least this amount for a further two and a half years.

Candidate Requirements

Applicants must satisfy the University of Oxford’s doctoral admission requirements. Assessment criteria:

• A strong undergraduate degree in Engineering, Computer Science or a related discipline

• A strong computational and/or engineering background

• Excellent written and spoken English communication skills

Contact Information

For information or an informal discussion: Professor Noa Zilberman (noa.zilberman@eng.ox.ac.uk) or the Centre (applied-ai@sbs.ox.ac.uk).

Application queries: postgraduate.admissions@eng.ox.ac.uk

Application Procedure

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details about application requirements, instructions and the online form are available on: DPhil in Engineering Science course page.

Please quote reference 27ENGIN_NZ in all correspondence and in your graduate application.

Application deadline: noon on Wednesday 2 December 2026 (In line with the December admissions deadline, set by the University)

Start date: October 2027