1,732 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" research jobs in United Kingdom
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experience in Mechanical Engineering, Applied Mathematics, Physics, Acoustics, Computational Science or a closely related discipline. Strong experience in numerical/computational modelling (e.g., FEM
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connected large wind energy system dynamic modelling, control and analysis. In particular, the objective of this research programme is to lay the foundations of a new, model and methodology for Advanced wind
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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Cranfield Campus, Cranfield, Bedfordshire Hours of work 37 hours per week, normally
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of CH previously developed in our group. About You We are seeking quantitatively-minded researchers with a PhD in physics, mathematics, computer science, mathematical/computational biology, evolutionary
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polymers, foams and composites The role is highly hands‑on and creative: you will manufacture new polymer formulations, refine processing routes, and carry out mechanical, fracture, thermal and
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spectrometry–based proteomic approaches, working closely with bioinformaticians to integrate molecular datasets with clinical metadata using advanced computational and systems biology methods, including
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of CH previously developed in our group. About You We are seeking quantitatively-minded researchers with a PhD in physics, mathematics, computer science, mathematical/computational biology, evolutionary
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and testing of LLMs. About you You will hold, or be close to completion of a PhD/DPhil in a relevant technical subject (e.g. computer science, statistics, engineering) and possess sufficient specialist
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well as a PhD (or equivalent level 8 qualification) in AI, Data Science, Computer Science, Biomedical Engineering, or related field, or equivalent experience. Please view the job description and person
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials