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View All Vacancies Engineering Location: Jubilee Campus Salary: £30,487 to £45,585 per annum (pro rata if applicable), depending on skills and experience (minimum £33966 with relevant PhD). Salary
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data analysis, statistical methodologies and machine learning for investigating complex diseases and should be driven by the translation of these data to addressing current biomedical challenges. Main
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mesoscale materials modelling to carry out meso-scale simulations of Li/Na dendrite growth and mechanical stress-strain behaviour of materials in solid-state batteries, and to develop machine learning methods
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of statistical privacy, distributed inference, and/or game theory would be useful, but are not expected. You should have, or be close to completing, a PhD in Statistics, Probability, Machine Learning or a related
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collaborators and travel to academic conferences and project meetings to present the work. Successful candidates must hold (or close to completing) a PhD in a relevant subject. Knowledge and experience in
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. The appointed candidate will also collaborate with researchers in Prof Tao Chen’s group for using machine learning methods. Candidates must hold (or be close to completion of) a PhD in Chemical Engineering
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candidates must hold (or close to completing) a PhD in a relevant subject. Knowledge and experience in computer vision is required. Experience of efficient ML techniques, edge AI hardware platforms, low-power
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publications, conference presentations and public engagement Essential Criteria Qualifications PhD, or equivalent research experience, in Computer Vision/ Computer Science, Visual Neuroscience, Psychology
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? Are you looking for a new and exciting challenge to develop innovative digital tools combining CFD and machine learning to reduce manufacturing-induced deficiencies of ceramics? We have a vacancy for an
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Intelligence and Machine Learning techniques Proficiency with Matlab and Arduino or similar programming languages such C/C++, Python, and JavaScript Understanding of integrated systems Ability to organise and to