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Field
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analysis and machine learning methods for optimisation and decision making, to describe the F&V supply chains for various products at regional UK scale and assess their resilience to cascading risks
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combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner health and behaviour
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Informal enquiries can be made to Dr Hazel Wilkinson, Deputy Director IDAI, email
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This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research
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About MINDS Centre for Doctoral Training The Machine Intelligence for Nano-Electronic Devices and Systems (MINDS), is a very successful £5M Centre for Doctoral Training (CDT) funding around 50 PhD
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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of the quantum machine learning task. You should have a strong background in theoretical physics, quantum computing, or machine learning and have completed or be in the final stages of a PhD in this or a related
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Knowledge of machine learning or multi-omics data integration would be highly desirable Essential Application/Interview Deep interest in musculoskeletal research and translational science Essential