52 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at UNIVERSITY OF SOUTHAMPTON
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multiple long-term conditions navigate their social care needs. The position is full-time fixed-term until 01/04/2026. About you You will hold a PhD or equivalent professional qualification and experience
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governance applications. The successful candidates will have a PhD (or nearing completion) or equivalent professional qualifications and experience in Cancer Care/Nursing /Health Services Research/related
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technologies and lithium-ion batteries. You will utilise our facilities to synthesis and characterise materials and devices for synchrotron experiments. We have developed cutting edge tools that include machine
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and translation. You will be based in the School of Electronics and Computer Science (ECS), working alongside an interdisciplinary team led by Dr. Shelly Vishwakarma (s.vishwakarma@soton.ac.uk), in
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should have required qualifications and experience Education: PhD in Biomedical Engineering, Electronic Engineering, Mechanical Engineering, Materials Science, or related disciplines with a strong academic
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extraction and data analysis. We invite applications from candidates who have a PhD or equivalent qualifications and experience in a quantitative field, such as Statistics, Medical Statistics, Health Services
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You will be directly involved with the UNIFORM (UNIfying Grid-FOllowing And Grid-foRMing Control In Inverter-based Resources) project, a collaborative programme with four academic and industrial
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will hold a PhD in a relevant discipline or equivalent experience. Candidates who are working towards a PhD will be considered for appointment as a Senior Research Assistant. Experience in undertaking
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an impact, apply to join our team! Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title
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Primary Ciliary Dyskinesia Group An exciting opportunity has arisen to join a national research programme with the aim of speeding up the diagnosis and treatment of rare respiratory diseases