438 engineering-computation-"https:"-"https:"-"https:"-"https:"-"UNIV"-"UNIV" Fellowship positions in United Kingdom
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your machine learning expertise to cutting-edge automated optimisation challenges? We are seeking a Research Fellow in Digital Chemistry and Engineering to combine self-optimising flow reactor technology
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members to ensure all project deliverables are met. Undertake these responsibilities in the project: i. Conduct comprehensive literature review on NQR technology, including design approaches, scanning
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on delivering high-quality teaching and diverse, real-world research. We specialise in biosciences, chemistry, computing and technology, as well as engineering, forensic science, mathematics, physics
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Honours degree in Computer Science/Mathematics/ Electrical and Electronic Engineering (or related discipline) Have, or be about to obtain*, a PhD in a relevant subject (must be obtained within 3 months
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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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Machine Learning Researcher to join a multidisciplinary team of fabrication engineers and AI specialists at the University of Southampton, within the School of Electronics and Computer Science, working in
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of future food and alternative proteins, priority areas of interest are highlighted below: Cultivated meat: examples include a research program on cell line development, cell engineering, process optimisation
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hydrodynamics. Have a degree in Naval Architecture / Marine Engineering / Ocean Engineering / Other Relevant Engineering Degree. Possessing a Master’s or PhD degree will be advantageous. Experience in any
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Computer Science, Engineering, Psychology or cognate discipline PhD, or in final stages thereof, in Computer Science, Engineering, Psychology, Safety Science or cognate discipline, or equivalent experience Knowledge
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to £43,805 per annum Apply by: 26/04/2026 Role Description We welcome applications from skilled, delivery-focused engineers to contribute to our successful railways-applied smart machines research programme