11 computer-programmer-"https:"-"https:"-"UNIS"-"LaTIM---Brest" Fellowship positions at KINGS COLLEGE LONDON
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professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six
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, Regeneration & Transplantation, and Paediatric & Rare diseases and a strong public and patient involvement and engagement programme. About the role The clinical research fellow will undertake research activities
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professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six
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already commenced training in general cardiology and wish to gain more sub-specialty experience in Cardiac MRI (CMR), by taking an Out-Of-Programme Experience (OOPE) from their current training programmes
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already commenced training in general cardiology and wish to gain more sub-specialty experience in Cardiac MRI (CMR), by taking an Out-Of-Programme Experience (OOPE) from their current training programmes
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, Regeneration & Transplantation, and Paediatric & Rare diseases and a strong public and patient involvement and engagement programme. About the role The clinical research fellow will undertake research activities
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program grant, REFUEL-MS, which is developing and evaluating a tailored digital treatment to help individuals with multiple sclerosis effectively manage their fatigue. You will be involved in analysing data
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articles, contribute to the teaching and learning programmes in the department, and gain additional development opportunities including supervision of postgraduate research students. The post holder will be
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the ability to translate between clinical and technical language while working with radiology informatics teams. A solid understanding of DICOM standards, PACS and RIS environments, GDPR, and image transfer
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental