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Physics, Theoretical physics, Maths or other closely related subject (e.g. Materials Science with evidence of strong computational background and skills). To apply, please contact the supervisors; Dr Thomas
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complex input. For instance, in physics-informed ML, in addition to data examples used by a standard ML setup, domain knowledge serves as an additional input. It can be in an explicit form of rigorous
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. This project offers a unique opportunity to contribute to both theoretical algorithm design and practical deployment in aerospace systems. Eligibility This studentship is funded through an industrial
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theoretical results with real embedded system demonstrators. A successful outcome of the project is a methodology for distributed control architecture design resulting in resilient aerospace propulsion systems
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to be probed by a combination of theoretical analysis and reverse engineering, in particular for operations that involve inputs and outputs in different formats. Currently, this probing must be done
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PhD Studentship: Microswimmers with Autonomous Propulsion Inspired by Biology and Designed with Physics Are you fascinated by working at the intersection of physics and synthetic biology? This PhD
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and democratic security and to explore the challenges that AI poses to democracy as a form of governance and to the security of electoral and other democratic processes. This will include theoretical
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. Investigating if and how classical systems can offer trustworthy, scalable, and efficient validation for quantum technologies is the crucial theoretical and practical challenge we aim to address. Our unique
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PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently
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Computational Chemistry methods to model enzymes and polymers. Designing and optimising novel biodegradable polymers. Integrating novel AI tools into the discovery process for new polymer candidates. Project