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Field
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Observatory, and LSST. Expertise in modeling cosmological observables through analytical methods or numerical simulations, machine learning, statistical inference, and data reduction is beneficial. As members
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postdoctoral research fellow in the area of computational soft matter physics. The main research tasks include developing new numerical methods for simulating self-assembly of anisotropic colloids. The Research
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apply approximation methods for interpolating electronic/phononic/thermodynamic properties of disordered crystal materials. Design and implement high-throughput density functional theory (DFT) workflows
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databases for ammonia, hydrogen, and hydrocarbon fuels; perform emission formation pathways analyses by simulation software; explore the application of low-emission ammonia combustion methods. Key
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databases for ammonia, hydrogen, and hydrocarbon fuels; perform emission formation pathways analyses by simulation software; explore the application of low-emission ammonia combustion methods. Key
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. Desirable Criteria: Interest in application of research to Defence and Intelligence domains, and collaboration with industry Familiarity with formal mathematical proofs and analytical methods, or numerical
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partners. The post holder will be responsible for developing and implementing mechanistic models, primarily using the Discrete Element Method (DEM), to analyse and predict pharmaceutical tablet
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The Post The aim of the overall RESPECT project is to produce data, methods, landholder tools and proposals for governance reforms to change agricultural practices on peatland and contribute
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analyzing numerical methods and/or machine learning methods for scientific computing. A strong computational background and experience with languages and frameworks such as Matlab, Python, NumPy/SciPy
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candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use this experience in collaboration with