28 assistant-professor-computer-science-data "https:" "https:" "https:" "https:" research jobs at Imperial College London in United Kingdom
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The Research Assistant will join an international interdisciplinary team funded through the British Heart Foundation Programme Grant (My Heart Counts). The role focuses on developing and maintaining
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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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We are seeking a Research Assistant to enrol in a 3-year Research Doctorate employed at the Department of Civil and Environmental Engineering, Imperial College. The post will carry out research as
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-year Research Associate or Research Assistant post in Computational Modelling of Cardiac Diffusion Tensor Imaging is available to further these methods. This project forms part of a BHF and EPSRC funded
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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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10 Mar 2026 Job Information Organisation/Company Imperial College London Department Department of Materials Research Field Engineering » Materials engineering Researcher Profile First Stage
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We are seeking a Research Assistant to join the multicentre Miro-Dose Experimental Medicine Trial, led by the Imperial College Small Vessel Disease Research Group, Department of Brain Sciences
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undergraduate, Masters and/or PhD students. You are further expected to publish findings, and help attract funding. PhD in Computer Science, Computational Bioengineering, Mechanical or Electrical Engineering
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, or even computational architectures. What we are looking for: Research Associate: hold a PhD (or equivalent) in Aerospace Engineering or a closely related discipline. Research Assistant: A first/masters
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(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as