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Research Studentship in Numerical Optimisation and Control 3.5-year D.Phil. studentship Project: Embedded Optimisation for Autonomous Spacecraft Control Supervisors: Prof Paul Goulart The project
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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degradation pathways. The project will be jointly supervised by Prof. Emma Kendrick (UoB), Dr. Tim-Patrick Fellinger (BAM), and supporting investigators. The student will split their time between both
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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career, whether in industry or academia. Please contact Prof. Isaac Chang (Isaac.Chang@brunel.ac.uk ) for an informal discussion about the project. Eligibility Applicants will have or be expected
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engage in immersive, simulated construction tasks, while wearable sensors monitor their physical effort, emotional states, and cognitive load. Physiological and behavioural data — including eye tracking
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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and social care research (Prof. Anderson), applied statistics and analysis of large routine datasets (Prof. Abel), and substantive knowledge of the abuse of older people and related policy issues and
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performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling
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abort (or not engage) if the bright white lines that fit a defined and rigid expectation are not clearly visible. These systems use algorithms, rather than AI machine learning, to detect road markings and