398 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" scholarships in United Kingdom
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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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, release kinetics under biologically relevant triggers. The successful candidate will work at the interface of organic synthesis, chemical biology, and machine learning to guide linker design and optimise
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Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/ ). The candidate will enrol for a PhD in Chemical Engineering at the University
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bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.04.2029 Reference no.: 5311 Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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project, please email Erika Mancini (e.mancini@sussex.ac.uk ) or John Spencer (j.spencer@sussex.ac.uk ) References: https://www.sussex.ac.uk/research/centres/sussex-drug-discovery-centre/ https
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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electron laser facilities. Contact: For informal enquiries please contact Sam Hay (Sam.Hay@manchester.ac.uk ) or Mike Hough (michael.hough@diamond.ac.uk ). https://www.manchester.ac.uk/research/sam.hay https
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nationally, statistics from 2019–2024 show that only around 26% progress beyond Entry level (CEFR A1; National Centre for Learning Welsh, 2025). Increasing these progression rates is a key aim of the Welsh