Research Studentship in Control Engineering and Energy Systems

3.5-year DPhil studentship 

Supervisors: Jack Umenberger 

This project concerns real-time balancing of energy in the electricity grid, a task essential for grid stability. The goals of the project are twofold. The first goal is to accelerate the solution of the large mixed-integer optimisation problems required to balance energy. Strategies will centre on improved formulations of the mixed-integer constraints, as well as the use of machine learning to accelerate conventional solution algorithms (e.g. branch and bound). The second goal is to handle the increasing uncertainty associated with high renewable penetration in a more systematic and effective way. Strategies will revolve around the application and extension of algorithms from online optimisation, including learning-augmented online algorithms.

This studentship is linked to the EPSRC project SORTED: Speedy Optimization for Real-time Energy Dispatch. The successful applicant will collaborate with project partners at the National Energy System Operator (NESO) and The University of Strathclyde. They will be a member of Oxford’s Control Group and Oxford’s ZERO Institute for zero-carbon energy research. As such, they will be supported by a multidisciplinary team of academic experts, with strong connections to industry, and will be able to collaborate widely with other researchers working in control, optimisation, and energy systems.

Eligibility

The studentship is open to Home students.

Award Value

Course fees will be covered at the level set for Home students. The stipend (tax-free maintenance grant) is the UKRI minimum stipend.

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 in any of Engineering, Materials Science, Computer Science, Physics, Mathematics.

• Excellent English written and spoken communication skills.

It is desirable that candidates possess expertise in some (but not all, or even most) of the following areas: 

• Applied mathematics, control engineering, and numerical optimisation

• Machine learning and/or data science

• Computer programming and/or software engineering

• Electrical engineering and/or power systems.

Application Procedure

Informal enquiries are encouraged and should be addressed to Dr Jack Umenberger (jack.umenberger@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 26ENGCO_JU 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