Research Fellow in AI & Optimisation for Physical Systems Full-time

Research Fellow in AI & Optimisation for Physical Systems

Duties for the Research Fellow would include:

• Develop, implement and evaluate novel optimisation, control, and machine learning methodologies including reinforcement learning, physics-informed machine learning, differentiable programming and model-based control to enable accurate and robust trajectory control in complex physical systems.

• Conduct simulation and experimental studies to assess the performance, scalability, and robustness of proposed control algorithms under realistic operating conditions.

• Publish and present research results in leading peer-reviewed journals and premier conferences in machine learning, optimisation, robotics, control, and computational science to disseminate findings and enhance the impact of the research.

From 1st August 2026 salary will have increased to:

£46,261 – £54,019 for Research Fellow

£39,807 – £42,891 for Research Assistants who are near completion

The position would be suitable for someone with a completed PhD (or close to completion) in Computer Science, Machine Learning, Physics, Mathematics, Statistics, Engineering or a closely related field, and with expertise and research interests in one or more of the following areas:

a) optimisation, control theory, machine learning, computational physics, or dynamical systems.

b) strong programming skills in Python and experience with modern scientific computing and machine learning frameworks, such as PyTorch, JAX, TensorFlow, or equivalent.

c) experience with numerical optimisation or physics-based simulation tools.

d) ability and willingness to work with hardware systems and to validate computational methods through practical implementation. The ideal candidate will also have the ability to create demonstrable and interactive computationally controlled prototypes.

As well as the exciting opportunities this role presents, we also offer some great benefits such as:

.41 Days holiday including bank holidays

.Hybrid working

.Final Salary Pension Scheme

.Cycle to work scheme and season ticket loan

.On-Site nursery

.On-site gym

.Enhanced maternity, paternity and adoption pay

.Employee assistance programme:

.Staff Support Service Discounted medical insurance.

As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women. You can read more about our commitment to Equality, Diversity and Inclusion here.