Research Studentship in Computer Engineering for AI-Driven Manufacturing

4-year D.Phil. studentship 

Project: Merging Datacentres into Manufacturing and Process Automation

Supervisor: Prof Noa Zilberman

Modern manufacturing and process automation floors are evolving into complex data ecosystems, mirroring the operational challenges of datacentres. As sensors generate vast data streams for AI-driven cell operations (Industrial-grade AI), the factory becomes a distributed computing environment requiring low-latency response, resilience, and energy efficiency. This research project addresses the challenge of developing e-Infrastructure for manufacturing that combines datacentre performance with the constraints of an AI-driven factory.

You will research emerging computing solutions for AI-driven manufacturing, covering aspects of network design and resilience, workload scheduling and deployment, and energy efficiency.

Eligibility

This studentship is funded through the UKRI EPSRC and Siemens and is open to Home students (full award – home fees plus stipend).

Award Value

Course fees are covered at the level set for Home students c. £10,470 p.a. The stipend (tax-free maintenance grant) is the UKRI Minimum Stipend c. £20,780 p.a. for the first year, and at least this amount for a further three years.

Candidate Requirements

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

• A first class or strong upper second-class undergraduate degree with honours (or equivalent) in Engineering or Computer Science
• Excellent knowledge in computer networks
• Excellent programming skills (C/C++, Python and scripting languages)
• Excellent English written and spoken communication skills

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)
• Good knowledge in distributed systems
• Previous experience in network simulation
• Previous experience in network drivers and tools
• Previous experience in distributed AI workloads
• Previous experience in industrial systems
• 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 this course page of the University website.

Please quote 26ENGIN_NZ2 in all correspondence and in your graduate application.

Application deadline: noon on 3 March 2026 (In line with the University admissions deadline set by the University).

Start date: October 2026