107 data-"https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" "UCL" "UCL" positions at Imperial College London
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may be required. For more information about the Pears Cumbria School of Medicine, please visit https://cumbriamed.ac.uk If you require any further details on the role please contact: Dr Lesa Kearney
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Are you an experienced clinical trials professional ready to make a national impact? Join the TRANSFORM study as a Data Manager and play a central role in delivering the UK’s largest prostate cancer
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– this includes Research Software Engineers (RSEs) and technical professionals working in data and computing infrastructure / High Performance Computing (HPC) roles. Led by Imperial College London, the project is
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As a Research Associate in Data-Driven Optimisation, you will work at the interface of chemical engineering, machine learning and automation, to develop next-generation workflows for the design and
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publications - Research statement (maximum 3 pages) - At least two letters of reference - InSpire Link Please contact Dr Andrea Mitridate andrea.mitridate@desy.de for any questions or more information
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-supervised by Dr Adria Junyent-Ferre and Professor Tim Green, and will work with engineers from the MVDC Technology team at GE Vernova. The candidate will spend time at Imperial as well as in GE Vernova's
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professional wellbeing . This is a full-time, fixed-term position based in the Dyson School of Design Engineering, supervised by Dr Billy Wu (https://profiles.imperial.ac.uk/billy.wu ). The post is available
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London in this area, go to: https://www.imperial.ac.uk/mechanical-engineering/research/ For information on how to apply, go to: http://www.imperial.ac.uk/mechanical-engineering/study/phd/how-to-apply
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, go to: https://www.imperial.ac.uk/mechanical-engineering/research/ For information on how to apply, go to: http://www.imperial.ac.uk/mechanical-engineering/study/phd/how-to-apply/ For further details
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Are you interested in shaping the future of global water modelling using AI? The Research Associate in AI-Enabled Hydrological Modelling and Data Assimilation will develop innovative methods