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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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-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
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a PhD in biology, earth system or data science, or a similar field, and have several years of experience with interdisciplinary collaborations focused on understanding biodiversity dynamics by
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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of the project in collaboration with national and international partners. The position is research-oriented but may involve teaching assignments. Qualifications Candidates must hold a PhD relevant to the academic
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the development of new research directions at the department. Your competencies You hold a PhD degree in Electrical Engineering, Control Engineering, Electrochemistry or a closely related field or can document
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of personal background, because we believe diverse perspectives and experiences improve research, support collaboration, and deepen our shared engagement with society. Qualifications Applicants must hold a PhD
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and supervision of students at the bachelor's, master's, and PhD levels. Qualifications for the postdoctoral position Academic qualifications at PhD level in animal or veterinary sciences. Research