19 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" research jobs at Imperial College London in United Kingdom
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outputs with electrochemical performance data from a variety of analytical techniques (e.g. diffusion, conductivity, power density etc) (D) Highly confident and articulate with outstanding communication and
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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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developing, documenting, and maintaining opensource software related to this project. Further information on the research of Dr. Marios Kogias can be found at https://marioskogias.github.io/ . Research
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Ministries of Health and partner research institutes across 24 countries, to improve understanding of dengue and Zika virus circulation and interaction (https://www.imperial.ac.uk/news/articles/medicine/school
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Practical experience of scanning electron microscopy including electron back scatter data processing and analysis (E) Highly confident and articulate with outstanding communication and persuasive skills both
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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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these representations to guide the identification, by debate, of (non-)compliance to PRLs of LLMs and T2Is; O3) in the case of non-compliance, using information conveyed in the debates to enforce PRLs on LLMs and T2Is
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‑bounded turbulence. This short, intensive 9‑month position offers an exciting opportunity to advance fundamental turbulence research using DNS/LES and data-driven optimisation techniques. In this role, you