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Collaboration (UKCRC)/ Modernising Medical Careers (MMC) integrated academic training pathway. The post forms an integral part of the Cardiology clinical academic training programme led by the Training Programme
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Honours degree in Physics, Engineering, Computer Science or related discipline (or equivalent) Essential Application PhD in medical image processing/analysis (or equivalent) Essential Application Experience
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background in theoretical physics and machine learning, and have completed or be in the final stages of a PhD in this or a related discipline. Main duties and responsibilities Design and analyse hybrid quantum
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Foundation-model-guided world models and predictive control for autonomous remote handling in extreme environments The Fusion Engineering Centre for Doctoral Training (CDT) PhD Research Project
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Stafford, at the University of Sheffield is leading a substantial research programme that will advance the translation of new medical device technology based on nanoscale hydroxyapatite, to address the unmet
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Stafford, at the University of Sheffield is leading a substantial research programme that will advance the translation of new medical device technology based on nanoscale hydroxyapatite, to address the unmet
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. The successful candidate will take forward their own programme of transformative research in the engineering and applications of novel biomedical sensing technologies that are underpinned by state-of-the art
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laboratory by identifying any requirements for computer-aided design equipment and equipment for rapid prototyping Identify suppliers for all the consumables and components required to prototype RF coils Setup
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)/Neurodegeneration clinical research programme. You will have the opportunity to be part of the NIHR Sheffield Biomedical Research Centre (Translational Neuroscience for Chronic Neurological Disorders) Junior Academy
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criteria in the application statement when you apply. Essential criteria– these will be assessed at application and interview stage Have a PhD (or equivalent experience) in the relevant field. Demonstrable