313 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral positions in United Kingdom
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including grade 7. Visit the [Centre for Research Staff Development](https: //www.kcl.ac.uk/research/research-environment/professional-development/centre-for-research-staff-development) for more
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Details: Clement.1.sefa-nyarko@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/404831/postdoctoral-resear… Requirements Additional Information Work Location(s) Number
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on https://www.durham.ac.uk/research/current/research-culture/ The Role Applications are invited for a Postdoctoral Research Associate in Theoretical Physics with a particular emphasis on the topic
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practices. Durham University is committed to the Concordat to support the career development of researchers. For further information please visit the Research Staff web pages on https://www.durham.ac.uk
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, Future Energy Systems and Advanced Materials, Electronics and Communications) and eight Research Nodes which group staff under technical expertise and interest (see https://www.durham.ac.uk/departments
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on https://www.durham.ac.uk/research/current/research-culture/ The Role Applications are invited for a Postdoctoral Research Associate in Mathematics with a particular emphasis on probability, statistical
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fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC
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application of AI and machine learning models to interpret complex X-ray datasets, and the integration of experimental and computational insights to generate actionable knowledge that advances sustainable metal
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situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and chemical information, enabling deeper understanding
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. The project integrates synthetic organic chemistry, kinetic analysis, automation, and machine learning to establish next-generation mechanistic workflows for asymmetric organocatalysis. The project advances