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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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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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, aerodynamic noise, machine learning, stochastic algorithms, uncertainties This University of Sheffield PhD project is part of the EPSRC Centre for Doctoral Training in Sustainable Sound Futures programme
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the development of this technology. In particular, the nonlinear and high-dimensional nature of the plasma dynamics mean that the desired reference state is challenging to compute and the control gains have to
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proofs, bounds, convergence results) alongside algorithm design and high-performance computation. Biological case studies, such as slime mould experiments, serve as inspiration and as a unique source of
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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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Reinforcement Learning from Human and AI Feedback (S3.5-COM-Peng) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Bei Peng, Dr Zheng Yuan Application
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potential diversion towards military applications. For example, the UK’s Spherical Tokamak for Energy Production (STEP) programme aims to deliver a prototype fusion power plant by 2040, which is expected
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in reviewing, testing, refining, and providing feedback on historical records that are automatically transcribed, coded, and linked using computer algorithms. Support the project and technical team in