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Application deadline: 8 January 2027 at 12pm (UK time) The UCL EPSRC Doctoral Landscape Award (UELA) is recruiting for approximately 50 fully funded, 4-year PhD studentships, starting in October
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to develop and implement state estimation algorithms, such as Kalman filters and observers, for real-time applications. Proficiency in MATLAB and Simulink for modelling, simulation, and validation using
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conduct cutting-edge research on the interplay of theoretical computer science, mathematics, and quantum mechanics. Particular topics include classical and quantum aspects of: Sublinear algorithms and
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persist across participants, and retraining from scratch is often computationally infeasible at scale. In this project, you will develop the next generation of federated machine unlearning algorithms
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candidate will design algorithms that identify suspicious model updates, reduce the influence of compromised UAVs, and preserve useful learning from honest UAVs operating with different data and unreliable
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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to evaluate and advance machine learning algorithms for one of the following application areas: “Characterising forests variations in relation to distance from pre-Columbian earthworks in the Amazon forest
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algorithms, validated in real-time simulations and experimentally in collaboration with industry. The project: This project looks at the development of electromechanical friction wheel braking (EMB) systems
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the University of Edinburgh, UCL and University of Bristol, and you will have the chance to work with researchers across our network at other UK universities. The PhD studentship would be co-located with
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algorithms. Vision Language Model (VLM) experience is desirable. Qualifications A high-grade undergraduate degree (first class or upper second) in computer science or MSc in related field. Skills Knowledge