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Computational Astrochemistry/Algorithm development for Quantum Dynamics Calculations School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD
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Computational Circular Design: Development, scalability and computational efficiency of surrogate-assisted many-objective optimisation algorithms for circular design for disassembly (C3.5-AMR
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Computational Circular Design: Development, scalability and computational efficiency of surrogate-assisted many-objective optimisation algorithms for circular design for disassembly (C3.5-AMR
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quality, avoiding the paralysis that troubles artificial algorithms when options seem equally good. This project asks: what objective functions do such biological systems optimise, and how can we use
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. Without these guarantees, the algorithms will remain limited to experimental testbeds. The aim of this project is to address this limitation by combining the complexity of deep-learning control policies
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, autonomous learning agents are likely to take an active role in human society, engaging in daily interaction and collaboration with humans. Developing learning algorithms that enable these agents to produce
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haptic guidance methods that respond to operator skill levels. Identify trajectory features that characterise expert performance for training robots. Develop algorithms that allow robots to refine
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algorithms using Monte Carlo simulation and Bayesian inference to distinguish normal tritium losses from suspicious discrepancies during transport, and to develop statistical thresholds that balance detection
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extraction? What would be the best choice of solvent? What is the optimal route to recycle the water in the fermentation broth? Answering these questions requires us to develop new design algorithms. It is