322 coding-"https:"-"FEMTO-ST"-"CSIC" "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in United Kingdom
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Commitment to open research, as appropriate to the discipline, through open data, open code, open educational resources and practices that support replication. Desirable: F1 Experience working with blood
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(multi-scale modelling experience desirable). Deep knowledge and understanding of composites mechanics. Practical experience and coding capability relevant to the aerospace sector is highly desirable
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integrate data from multiple sources—including tipping bucket rain gauges, weather radar, and satellites—using robust coding and data science techniques. A comprehensive quality control framework will be
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. The team also produces a Guidebook that collects team's practices and useful information at https://guidebook.devops.uis.cam.ac.uk/ Ideally you will have experience in: Designing and solving complex business
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: https://events.teams.microsoft.com/event/376b2195-d8da-47c0-86e2-b18813ec19e3@4a5378f9-29f4-4d3e-be89-669d03ada9d8 . Number Of Awards 1 Start Date 1st October 2026 Award Duration 3.5 years Application
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Contribute to further developments of the COLIBRE code This post is fixed term for 12 months from the start date. Successful applicants will, ideally, be in post before April 2026. Where to apply Website https
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about the MLTC CNC: https://www.nihr.ac.uk/about-us/what-we-do/multiple-long-term-conditions/collaboration Information about the AGE Research Group https://research.ncl.ac.uk/ageresearchgroup/ Key
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CountryUnited KingdomCityEdinburghPostal CodeEH9 3JGStreetKings BuildingsGeofield Contact City Edinburgh Website https://eng.ed.ac.uk/research/institutes/iie Street King's Buildings Postal Code EH9 3JG STATUS
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candidates are required to bring with them identification documents and original documents that prove they hold or can obtain the right to work in the UK. You can check your eligibility here: https
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proficient programming skills. Essential experience includes developing Discrete Element Models (DEM) or hybrid models (e.g., DEM-CFD, DEM-SPH). A proven research record through publications and code