195 machine-learning "https:" "https:" "https:" "https:" "U.S" Postdoctoral research jobs in Denmark
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targeted at career development for postdocs at AU. You can read more about it here: https://talent.au.dk/junior-researcher-development-programme/ If nothing else is noted, applications must be submitted in
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and postdoc cohort positions at http://www.capex-p2x.com . The research area will be within design and modeling of pulsed power supplies utilizing power electronics technology for plasma generation
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national and international collaborations and access to world-class infrastructure. Lab website: https://www.sahu-lab.com/index.html Department of Molecular Medicine (IMM) The Department of Molecular
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collaborative relationships. Read more about the Department of Food Science at: https://food.au.dk/ The place of work is Department of Food Science, Aarhus University, Agro Food Park 48, Skejby, 8200 Aarhus N
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Application deadline December 1, 2025, at 23:59 CET Apply online https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/jobs/preview/3144
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(written and spoken). Conduct independent research. Have high self-motivation to learn. Be able to work well and communicate expert knowledge in an interdisciplinary team. Have a strong sense of
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capabilities for batch analysis, visualization, and management of high-throughput experimental data based on the open-source NOMAD database model (https://nomad-lab.eu/nomad-lab/ ) Regularly and proactively meet
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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(e.g. using COBRApy or related toolboxes), or a strong motivation to develop this expertise. Data science, AI/ML, and digital surrogate models Experience with data science and machine learning, including
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration