359 data-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs in Denmark
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processing historical data, and the tasks will be relevant to the your further course of study. We are looking for a student who: Has strong quantitative skills Is proficient in Excel, Stata, and either R
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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to diversity and inclusion, and success in mentoring. Place of work The place of work is the Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark. Contact information
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to diversity and inclusion, and success in mentoring. Place of work The place of work is the Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark. Contact information
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environment. There is overall a close collaboration between the academic and the clinical staff at DCPT. About the research project The research project of this postdoc will be based on follow-up data from a
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employment is 21 months. Expected starting date is 1 June 2026, or according to mutual agreement. You can read more about career paths at DTU here . Further information Further information may be obtained from
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for the position in question is a broad ranging of techniques ranging from spatial and single-cell analyses to classic methods like histology cell culture and Western blotting. Data handling through bioinformatics
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evaluation using nasal epithelial models and tissue Contribute to in vivo validation in an established mouse model of acute seizures Analyze pharmacokinetics, biodistribution, and therapeutic efficacy data Co
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industry-facing research collaboration and coordinate cross-partner workflows in planning, data-sharing, and iterative decision-making across industrial and academic stakeholders. Teach and supervise PhD