255 coding-"https:"-"FEMTO-ST"-"UNIVERSITY-OF-BUCHAREST" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions in Sweden
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. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14445&rmlang
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. Where to apply Website https://lu.varbi.com/en/what:job/jobID:906273/type:job/where:39/apply:1 Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent Research FieldMedical
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at least three of the following Python libraries: TensorFlow, PyTorch, JAX, RDKit. Previous experiences with collaborative coding with GitHub Previous experience with cloud-based platforms About the
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, including participation in regular group meetings and events. You can read about the workplace: https://liu.se/en/organisation/liu/ifm/mdesign The employment This employment is a temporary contract of two
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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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reality. The person taking this position will be working with the team at the computer science and engineering department mostly on the performance engineering and hardware-aware code optimizations
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). Link to log in and apply https://kth.varbi.com/se/what:job/jobID:880654/ About the employment The position offered is for, at the most, two years. A position as a postdoctoral fellow is a time-limited
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results your qualifications and ability to realise the project Where to apply Website https://lu.varbi.com/en/what:job/jobID:905213/type:job/where:39/apply:1 Requirements Research FieldReligious
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contact with staffing and recruitment companies as well as sellers of recruitment advertisements. Where to apply Website https://www.hb.se/en/about-ub/work-at-ub/job-vacancies/ Requirements Research
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models