36 coding-"https:"-"FEMTO-ST"-"CSIC" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "St" Postdoctoral positions at University of Oxford
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found in the job description, and why you would like to do this role. See guidance at https://www.jobs.ox.ac.uk/cv-and-supporting-statement. Any technical questions related to this vacancy can be sent
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on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 12:00 midday on 16 January 2026 It is anticipated that interviews will take place on 5 February 2026
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University pages on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 12:00 midday on 16 January 2026 It is anticipated that interviews will
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carried out in collaboration with Prof. Susan Lea FRS FMedSci at St. Jude Children’s Research Hospital, and the successful candidates will have the opportunity to spend periods at St. Jude in Memphis, USA
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undertaking observations or focus groups setting up surveys in web-based survey tools and collecting online data support in developing and writing up case studies coding transcripts which may include developing
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ability to write clean, well-documented analysis code. Ability to work with EEG data and apply multivariate methods to extract meaningful measures relevant to memory and consolidation. Skilled in developing
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discrete dislocation plasticity modelling of metals and a good knowledge of dislocation plasticity and solid mechanics. Fortran coding experience and knowledge of Abaqus, Fortran user subroutines and crystal
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, computer science, statistical or population genetics, or a related discipline), and a strong motivation to work on problems in genetics and you will also have relevant coding experience with producing high-quality
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a TOTUM card, by showing an employee pass in selected local stores, or online by using any of the listed discount codes Childcare services - We offer excellent childcare services including five
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learning in chemistry would be advantageous, as would familiarity with ML approaches for atomistic modelling (e.g., MACE, ACE, NequIP, PhysNet, reactive MD). Prior contributions to scientific code