44 machine-learning "https:" "https:" "CMU Portugal Program FCT" Postdoctoral positions at KINGS COLLEGE LONDON
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
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or Python and version control systems like Git. Familiarity with spatial and statistical libraries (e.g. INLA, PyMC, scikit-learn, GeoPandas). Proven ability to work independently. Track record in publishing
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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
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, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub, workflow automation, documentation) Capacity to work
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to work on an NIHR-funded project evaluating Care (Education) and Treatment Reviews (C(E)TRs) for people with a learning disability and autistic people (the OptiCaT project). C(E)TRs were introduced in 2015
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skills. Aware of the ethical issues around working with Big Data. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in
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Formstone (see Panousopoulou et al. J. Cell Sci. 2016 (https://doi.org/10.1242/jcs.180703) and Prof. Philippa Francis-West (Mao et al. Nature Comms. 2016 (https://doi: 10.1038/ncomms11469 and Prof. Philippa
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at King's, which brings together a unique range of internationally recognised scientists and clinicians from across the School and King’s College London. More information: https://www.kcl.ac.uk/scmms About