358 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" PhD positions in United Kingdom
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devices for medical imaging and reaction monitoring, as well as for the development of sustainable photocatalysts. In this role you will develop machine learning (ML)-accelerated quantum mechanics in
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results is desirable. To be considered for this PhD, please follow the instructions here: https://www.centre-ub.org/studentships/application-process/ Application deadline: February 17 2026 Interviews
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The always-on, safety-critical nature of air traffic control raises rich and exciting challenges for machine learning and AI. The University of Exeter in partnership with NATS, the UK’s main air
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reservoirs. By embedding governing equations and boundary conditions directly into machine-learning models, the project aims to enable efficient exploration of high-dimensional parameter spaces without
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the supervisor’s complimentary research expertise in this area (https://millerresearchgroup.co.uk & https://www.lovelockresearchgroup.co.uk),[8,9 ] this PhD will involve the design and chemoenzymatic synthesis of a
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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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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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channel. This will be followed by designing a new resilient waveform for UOWC and developing a computer-based simulation to evaluate its performance. Finally, the study will use existing UOWC channel
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling