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interdisciplinary academic profile that combines competencies in energy systems analysis with qualitative social sciences methods, political sci-ences or similar. You possess strong analytical skills and experience
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the position. Your work tasks You will develop and validate digital-twin and optimization methods for electrolysis systems, working both independently and collaboratively with the group and with academic and
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be to develop wireless sensing and communication methods that are designed together with AI-based inference, rather than treating connectivity as a separate layer. Particular attention will be given
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that explain how humans learn, adapt and stabilise navigation behaviour in urban environments. The project will combine methods from transportation science, artificial intelligence, computational neuroscience
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are looking for candidates interested in developing new machine learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this position, you will
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. The project description must include: a presentation of an original research question a description of the initial theoretical framework and method a presentation of the proposed empirical material a work plan
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be to develop wireless sensing and communication methods that are designed together with AI-based inference, rather than treating connectivity as a separate layer. Particular attention will be given
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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, and energy storage in Denmark. As a professor you are expected to play a leading role in developing our expertise within applied basin research, seismic interpretation methods and our understanding
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perspective Familiarity with design-based, quantitative, qualitative, or mixed-methods educational research A solid foundation in digital research and/or learning technologies, experience working with