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Full time: 25 Hours per week Fixed term: 12 months We are looking for a candidate to join the University of Edinburgh to conduct research on Machine Learning, Reinforcement Learning, or LLM orchestration, with applications to Finance. This post is advertised as full-time (35 hours per week). We...
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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including discounted membership for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme. • On site nursery is available plus access to holiday camps
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interdisciplinary research programme involves national and international collaborators. We are a vibrant, enthusiastic, innovative and strategic enterprise with an internationally leading position to make a real
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C and python, familiarity with
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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to artificial intelligence (AI) (e.g. computer science, engineering, Statistics, and mathematics etc.) The post is available for 30 months, starting on 1 September 2025. If you are still awaiting your PhD to be
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Science Park. The post is funded by Innovate UK and is fixed-term to 30th April 2026. The CEBD project is an ambitious programme to develop the first category enhanced battery powered eVTOL. The project
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve