362 data-"https:" "https:" "https:" "https:" "https:" "https:" "University of New Hampshire" research jobs in Denmark
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tasks include planning, conducting, and publishing epidemiological studies using large-scale observational data, primarily register-based, focusing on women’s short- and long-term health outcomes within
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. Starting date is 15 April 2026 (or according to mutual agreement). The position is a full-time position. You can read more about career paths at DTU here . Further information Further information may be
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how geometry- and data-driven digital twins of wireless environments can support learning, inference, and coordination in physical AI systems such as robots, vehicles, or distributed sensing platforms
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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. The research project consists of studies that will be based on data from the Danish National Birth Cohort and the National Child Health Register. Your job responsibilities As Postdoc in Epidemiology your
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experiments on the behavior of emerging contaminants in porous media Performing quantitative data analysis and interpretation of experimental results Working in close collaboration with modelling activities
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
to ensure moisture-robust designs. In addition, competencies in data processing and integration, assessment criteria development, and practical construction knowledge are necessary to translate research
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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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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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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