Antonis Papachristodoulou
Top university
4 days ago
PhD Studentship in Data-driven Control Engineering for Large-scale Uncertain Systems University of Oxford in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Dec 2, 2026
Country
United Kingdom
University
University of Oxford
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About this position
PhD/D.Phil. studentship at the University of Oxford in Control Theory, Optimization and Learning, focused on data-driven control engineering for large-scale uncertain systems.
This project sits at the intersection of control engineering, optimization, statistical learning, and AI. The research aims to address core challenges in modern control design, including scalability, efficiency, robustness guarantees, and the use of emerging “world models” to extend traditional modelling frameworks. Potential work may involve developing control-theoretic and AI methods for reliable, robust control systems and applying them to large-scale uncertain systems.
The studentship integrates with research activities connected to the new MSc in AI for Engineering Biology in Oxford’s Department of Engineering Science. Successful candidates will join a multidisciplinary environment and may collaborate with academic and industrial partners nationally and internationally. The project offers training in theory, algorithm design, engineering, and the application of control methods to AI technologies, with career pathways in academia, bioscience industry, and entrepreneurship/start-ups.
Funding: full award for UK students, including home fees and a stipend. Course fees are covered at the UK rate (at least £10,940 per year). The stipend is at least approximately £21,805 per year for the first year and continues at that level for a further two and a half years. There may be flexibility to support international students, but applicants from outside the UK should contact the supervisors before applying.
Eligibility: applicants should have a first-class or strong 2:1 degree in Engineering, Computer Science, Physics, or Mathematics, and strong English communication skills. Relevant experience in control engineering, AI, mathematics, robotics, or software/programming is desirable.
Deadline: noon on 2 December 2026. Start date: October 2027.
Apply via: the University of Oxford graduate application system using the Apply button on the posting page. Quote reference 27ENGCO_AP in all correspondence and in the application.
Funding details
Available
What's required
Applicants should have a first class or strong 2:1 degree in Engineering, Computer Science, Physics, or Mathematics. Excellent written and spoken English is required. Desirable background includes some experience in Control Engineering, Computer Science, Artificial Intelligence, Applied Mathematics, Electrical or Mechanical Engineering, Robotics, and Programming/Software Engineering. International students may be considered if supervisor flexibility is available; candidates should contact the supervisors to confirm eligibility.
How to apply
Submit a graduate application form via the Apply button on the University of Oxford course page. Quote 27ENGCO_AP in all correspondence and in your application. Informal enquiries can be sent to Antonis Papachristodoulou and Kostas Margellos by email.
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Professors
Prof at University of Oxford
United Kingdom
Research Interests
Control System
Artificial Intelligence
Synthetic Biology
Optimal Control
Biomedical Engineering
Prof at University of Oxford
United Kingdom
Research Interests
Behavioral Economics
Microeconomics
Robust Control
Distributed Algorithms
Multi-agent System
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.