397 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" scholarships in United Kingdom
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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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for the computer simulation of electronically excited processes in molecules and materials. In the age of net-zero it is more important than ever to obtain a deep, molecular-level understanding of the working
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Research Council rate (set at (£21,805 p.a. for 2026/2027 academic year) for 3 years. Please note the eligibility criteria set out by the UKRI at: https://www.ukri.org/what-we-do/developing-people-and-skills
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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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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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Science, Machine Learning, Finance, FinTech, Economics, or a related field. Candidates should demonstrate knowledge of Large Language Models, generative AI, and machine learning, with interest in financial
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to commence on 1st October 2026 are now open at the School of Physical Sciences. The projects available are listed here: https://www.open.ac.uk/science/physical-science/phd-students/current-phd-studentships
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PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis for synthesis. A doctoral position is
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the