38 computer-programmer-"IMPRS-ML"-"IMPRS-ML" Postdoctoral positions at KINGS COLLEGE LONDON in United Kingdom
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work closely with Prof. Hanna Kienzler, Prof. Stephani Hatch, and Dr Rebecca Rhead as part of the Centre’s ‘Marginalised Communities’ programme. This involves partnering with Black and racially
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supervisor), working with Dr David Watson (Department of Informatics). This position is funded by King’s Climate and Sustainability. The key responsibilities of the role are to develop machine learning
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of York. Based within the Addictions Department at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN), the post-holder will support a five-year programme of research across three priority areas
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research methods (including research ethics, interviewing, and analysis using software programmes such as NVivo. Strong experience in community engagement (preferably with minoritised ethnic people
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will join a team of researchers, clinicians, and patient partners on a 5-year collaborative research programme funded by a Wellcome Mental Health Award, ‘When your body betrays you: interoceptive
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& wider impact work). Secondly, you will do qualitative research with Prof. Ben Geiger and Prof. Karen Glaser as part of CSMH’s programme on ‘Work, Welfare Reform and Mental Health’. In particular, you will
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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women's health. We also have thriving research programmes in global health, and health and social care. Further information about the Faculty of Life Sciences and Medicine may be found at https
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development laboratories at Guy’s Campus, London Bridge. The group specialises in inventing custom fluorescence-lifetime and multiphoton technologies and coupling them with powerful computational pipelines
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of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse single-cell modalities, focusing on gene