510 data-"https:"-"https:"-"https:"-"https:"-"Edinburgh-Napier-University" positions in Denmark
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe
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on the platform ARTIQ (ARTIQ ) Application deadline The application deadline is the 1st of May 2026 Contact information Further information can be obtained from Michael Drewsen ( drewsen@phys.au.dk ) Formalities
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against
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sensing and autonomous systems into geospatial analysis? Do you thrive in interdisciplinary environments and enjoy combining data-driven research with hands-on fieldwork — whether on boats, underwater
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at DTU here . Further information Further information may be obtained from Senior Researcher Dennis Christensen, dechr@dtu.dk , +45 20961946. You can read more about our department DTU Energy at
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, organoid-based models and in vivo cancer and infection models Integration and analysis of transcriptomics and proteomics datasets Establishment and maintenance of standardised experimental pipelines Data
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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Information Further information about this position is available via email from Professor Ahmad Rafsanjani (ahra@mmmi.sdu.dk ). If you experience technical problems, please contact our email support
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degree or equivalent within Public Health, Medicine, Data Science or other fields related to Epidemiology or Environmental Medicine. The ideal candidate has prior experience in working with health data, is