220 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" Postdoctoral research jobs in Denmark
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about DTU Electro at www.electro.dtu.dk . For more specific information on the Quantum Light Sources group, see also https://electro.dtu.dk/research/research-areas/nanophotonics/quantum-light-sources
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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive
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@dtu.dk You can read more about DTU Space and the division of Astrophysics and Atmospheric Physics at https://www.space.dtu.dk/english/ If you are applying from abroad, you may find useful information
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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. Further information Further information may be obtained from Prof. Ivan Mijakovic: ivmi@biosustain.dtu.dk You can read more about the hiring department at https://www.biosustain.dtu.dk/ If you are
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at scientific conferences. Excellent English skills, both written and oral Who we are You will be part of the Section for Microbiology. To find out more about who we are check the following page: https
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. Who we are The project is led by Jesper Asring Hansen, Associate Professor at Aalborg University and principal investigator of POLSAFE (see profile: https://vbn.aau.dk/da/persons/jajh/ )The research
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include: Supporting the delivery of the 3D-CIRCULAR master and doctorate programmes, including coordination of hybrid (online/in-person) teaching and supervision activities. Updating and refining learning