8 finite-element-methods Postdoctoral positions at Heriot Watt University in United Kingdom
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tools are need during the development of new imaging and sensing systems. With the rapid deployment of data-driven methods, repliable uncertainty quantification remains a big challenge that requires
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future industrial laser chassis, utilising powder-bed laser fusion metal additive manufacturing (AM) and advanced laser-based manufacturing. The project is split into four areas: 1. Optical, mechanical
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of novel, high symmetry polymetallic cages of paramagnetic transition and lanthanide metal ions, including organic and inorganic syntheses, single crystal and powder XRD, and all associated data analysis
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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have
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-laser-welding of optical laser components to structural components (ps- and fs-pulsed lasers) Advanced utilisation of powder-bed laser fusion metal additive manufacturing. Test methods of evaluating
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quantum field theories, and the application of Hamiltonian methods to gauge theories, though you will also be encouraged to develop and pursue your own research directions. Applicants should have a PhD in
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the context of teaching and supervision duties. Could be expected to contribute to specialist courses such as research methods and equipment. Develop research objectives and proposals for own or joint research
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candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation theory, and/or (ii