201 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions in United Kingdom
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experience in the use and/or development of machine learned interatomic potentials would be seen as a significant asset. Previous experience of inelastic neutron scattering spectroscopy (or similar) would be
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The job information is shown below. Please click on the links to see full details. The Centre for Appearance Research (CAR) is looking to appoint a part time Research Fellow (0.6fte) to join a
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good collaborative skills within a team. You may also have strong theoretical and programming background in AI, machine learning, mathematical modelling including physics-based models, and/or robot
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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computers”(under the UKRI Guarantee scheme). Topics include: Quantum many-body dynamics Quantum algorithms Quantum-enhanced numerical methods Quantum machine learning Tensor Networks Topological order The
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The Centre for Appearance Research (CAR) is looking to appoint a part time Research Fellow to join a team of researchers on a fixed term project, funded by The Scar Free Foundation ; evaluating a
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emerging multi-omic measurements to build and test machine-learning-based multimodal risk prediction tools. A key element of the role will be to explore how different data types and AI-derived features can
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly
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and senior members.” “Like our founders, we want to transform the College and, through it, the lives of the people who come to learn, to teach and to do research. And through them to change society for