217 machine-learning "https:" "https:" "https:" "https:" "https:" "Bournemouth University" Postdoctoral positions in Denmark
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
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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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requirements, including link budgets, beam steering, and orbital pointing dynamics. • Experience with optimization methods and physics-informed machine learning. • A strong publication record in antennas
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research profile within organisational studies, Computer-Supported Cooperative Work, Human-Computer Interaction or related research areas as documented by a PhD dissertation and/or research publications
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experimental and suited for candidates who enjoy hands-on research, learning new techniques, and working across disciplinary boundaries. Your competencies We seek a highly motivated candidate with a strong
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sedimentary archives, to facilitate and use in-situ and remote sensing observations of polar environments, and to acquire skills within VibroSeismic data acquisition, analysis and interpretation. The position
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. We expect applicants to hold a PhD in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, human-robot interaction, digital health, anthropology
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orthopaedic surgery. This role combines medical imaging (ultrasound and MRI), computer-assisted surgical technologies, and the study of how bones and joints move. The targeted starting date is March 1, 2026
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development for postdocs at AU. International applicants International applicants are encouraged to learn about the attractive working conditions and other benefits of working at Aarhus University and in