25 data "https:" "https:" "https:" "https:" "Dr" "UCL" research jobs at Imperial College London in United Kingdom
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data pipelines for smartphone, wearable, molecular and clinical datasets to advance early detection and monitoring of pulmonary arterial hypertension. You will work closely with computational scientists
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personal monitors of cardiovascular health. Further information on the research themes: https://www.imperial.ac.uk/bhf-research-excellence/ . Recruitment is open to expertise in all relevant areas including
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David Muller. For further information or to arrange an informal discussion please contact Dr Eduardo Seleiro (e.seleiro@imperial.ac.uk ). To apply, please complete and upload the form available from ICL’s
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Prof. Stefano Angioletti-Uberti s.angioletti-uberti@imperial.ac.uk For more information, please visit https://www.glycocalyx.org/ Please see the advert on https://euraxess.ec.europa.eu/ Closing date
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months in the past three years. Additional Information Work Location(s) Number of offers available1Company/InstituteImperial CollegeCountryUnited KingdomGeofield Contact City London Website http
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. Constantinides and Dr Dan Goodman, who each bring leading expertise relevant to this research programme. You will implement models in software frameworks for neural simulation and machine learning, and work with
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neurodegenerative disorders. The role centres on enabling high-quality, reproducible analysis across prescription data, longitudinal clinical records, wearable time-series data, and multi-omics datasets, with
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by Professor Ara Darzi, while working towards a PhD degree . The research project will entail project design, experimental work in addition to data analysis and reporting the results in peer-reviewed
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by the Medical Research Council, that aims to improve the standardisation, modelling, and analysis of prescription data in Parkinson’s disease, with the goal of predicting medication-related side
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Associate (post-doctoral) is to conduct world-leading research on Neuro-Symbolic Debates for Safeguarded Generative AI, under the direction of Prof Francesca Toni, in collaboration with Dr Soteris Demetriou