252 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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PhD Studentship in Aeronautics: Real-time machine learning and optimisation for extreme weather (AE0073) Start Date: Between 1 August 2026 and 1 July 2027 Introduction: Climate change is
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. The National Centre for Suicide Prevention and Self-harm Research (NCSR) is tackling these barriers by putting together a world-leading data resource on suicide and self-harm, and powerful machine learning
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You will receive project-specific training in numerical modelling tools and techniques and in machine learning. Eligibility requirements If you have received a First-class Honours degree, or a 2:1
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for representing and combining multimodal information over time. Grounded in machine learning, representation learning, and efficient algorithms, the work addresses real-world challenges in sustainable and
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We are recruiting a new fully-funded PhD student to join Dr Daniel Yon’s Uncertainty Lab at the School of Psychological Sciences at Birkbeck, University of London. This post is attached to a recent grant awarded to Dr Yon from the Leverhulme Trust entitled Public Communication and Private...
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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
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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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that can be run. Emulating expensive processes could allow more data to be generated from better models, at lower cost. The central science question is: how can machine learning and evolutionary computation
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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/10.1021/acs.jpcb.4c01558 ], but they lack accuracy for predictive modelling. Transferable machine learning potentials, like MACE-OFF [https://doi.org/10.1021/jacs.4c07099 ], effectively achieve quantum