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Field
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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modelling and related research topics. Develop, implement and validate computational simulation models for impact and injury prediction using appropriate numerical methods and software tools. Design and
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focus on the area of computational mathematics broadly construed. This includes optimization, mathematical foundations of machine learning and AI, AI for mathematics, and numerical analysis. Demonstrated
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biomedical engineering. Design and optimize three-dimensional printed structures using computer-aided design, numerical modelling, data-driven optimization, and artificial intelligence-assisted methods
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and predictions. Use cutting-edge methodologies such as A.I. and machine-learning to accelerate the numerical simulation processes. Develop optimal control strategies for energy systems Publish high
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scale and the sample scale. - Establish links between microstructure and mechanical properties, by combining experimental and numerical approaches, with the aim of optimizing material performance. Within
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, numerical optimization) applied to an engineering problem, preferably in your master's thesis. Prior exposure to (projective) geometric algebra is a plus but not expected - willingness to master new
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using pumping systems coupled with rainfall replenishment in sand-filled reclaimed land. The research will combine 1-g physical model testing with analytical and numerical modeling to design optimal
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The successful candidate will work with Asst. Prof. Shen Shuting on combinatorial inference under a project on "Post-learning inference for near-optimal discrete structures". The main
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, CUDA), numerical linear algebra, sparse matrix computation, and low-latency system design. · Machine Learning and AI Theory/Algorithm Design: optimization theory and algorithm design for deep learning