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, advanced imaging techniques and numerical modelling. About the role A successful candidate will be working on the EPSRC funded project New perspectives in photocatalysis and near-surface chemistry: catalysis
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, advanced imaging techniques and numerical modelling. About the role A successful candidate will be working on the EPSRC funded project New perspectives in photocatalysis and near-surface chemistry: catalysis
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-quality teaching. The Hub for Applied Bioinformatics (HAB) is the Faculty’s focal point for computational biology, delivering bespoke bioinformatics support and training across genomics, transcriptomics
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-quality teaching. The Hub for Applied Bioinformatics (HAB) is the Faculty’s focal point for computational biology, delivering bespoke bioinformatics support and training across genomics, transcriptomics
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development. The successful candidate will have a MSc or equivalent experience in a relevant discipline (e.g., computer science, clinical informatics, software development, knowledge representation, machine
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or bioinformatics and a keen interest in cancer biology. Extensive and demonstrated experience in scRNA-seq, spatial transcriptomics, with image analysis experience an advantage. A proven publication
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environment within the Division of Thoracic Surgery, as well as the Cancer Research Program of the RI-MUCH, the Goodman Cancer Institute, and the Biomedical Engineering Department at McGill University
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individual and collective wellbeing. Employee support at King’s includes flexible working arrangements, paid maternity/shared parental leave, menopausal support, an active wellbeing programme, training and
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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for Translational Informatics ( www.ctiuk.org ) and actionable analytics theme of the recently awarded Health Data Research UK (HDR UK) London site. Major funding has been awarded by the Office for Life Sciences