23 data-"https:" "https:" "https:" "https:" "UCL" "UCL" "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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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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application of these methods using data collected as a part of the Discern project. You will contribute to the development of the epidemiological and analytical plans, conduct the data analyses, interpret
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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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to the broader Innovation and Knowledge Centre mission to help bridge the gaps between academic research and industrial impact in this field. A strong background in machine learning, computer engineering, applied
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transmission dynamics. The post will support quantitative research using routine electronic health record data from primary care and hospitals, as well as data from the clinical trial to assess the impact of
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gas challenges. You will particularly gain skills in the principles and practice of running mechanistic clinical studies from practical aspects through to handling data. In addition to supporting
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and managing aspects of an academic lab Proven track record of research in their area of expertise on alternative proteins or closely related area Experience in analysing biological experimental data