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Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee if necessary, – the head of department selects the candidates to be evaluated. All applicants will be...
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
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collaboration between the Department of Electrical and Computer Engineering and the Novo Nordisk Foundation CO2 research center, Aarhus University, we aim to address this opportunity by developing digital twins
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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it will also involve a small degree of teaching and supervision. To that end, the successful applicant will be expected to take part in the department’s teaching and supervision activities and to teach
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teach and supervise at BA and MA levels at the Department of Digital Design and Information Studies. Given the international focus of the degree programmes, the successful applicant will be expected
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You have academic qualifications at PhD level, for example within the areas of bioinformatics, machine learning or forensic odontology. We favour experience in computational data analysis, and the
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to assess stakeholder needs, create PV-integrated sensors to monitor agriculture-specific stressors, model stress impacts on PV performance, and develop innovative PV tracker controls. These elements will be
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the foundations for reliable decision support and Monitoring, Reporting, and Verification (MRV) systems for reducing greenhouse gas emissions in Danish agriculture, particularly exploring conditions for the uptake
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combines neuroscientific, musicological and psychological research in music perception, action, emotion and learning with the potential to test prominent theories of brain function and to influence the way