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bachelor’s, master’s and PhD degree programs within animal science and veterinary medicine. We offer a lively, engaged and innovative learning and study environment, which is closely integrated in the research
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
the international focus of the degree programmes, the chosen applicant will be expected to teach in English as well as Danish. Qualifications Applicants must have a PhD degree or must document equivalent
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: Overcoming Inequity in Embodied Learning in Danish Vocational Education and Beyond, funded by Independent Research Fund Denmark. This is a full-time (37 hours per week), fixed-term (24 months) postdoctoral
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consist of the PI, one postdoc and one PhD. Read more about the project here: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders/eksterne-personer-en/research-leaders-2025/mathias
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teaching and supervision of bachelor's and master's students in areas related to your expertise. Your competencies We expect you to have: A PhD in electrical engineering, energy engineering, mechanical
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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply
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have: A PhD in electrical engineering, energy engineering, mechanical engineering, control engineering, operations research, applied mathematics, or a closely related field. Documented experience in
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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need to have a PhD in marketing, consumer behaviour, psychology, behavioural economics, environmental psychology, or another relevant field. Demonstrated experience designing, fielding and analysing
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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how