48 affective-computing-emotion Postdoctoral positions at Technical University of Denmark
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and bio-technological informatics, metagenomics, epidemiology, integrative systems biology and machine learning. The research at DTU Bioinformatics is focused on bioinformatics and computational
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Nordisk Foundation and led by Associate Professor Mikkel Schmidt (DTU Compute). In LightTrap , we will use AI to accelerate the discovery of new optical materials and that enhance the performance of thin
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Job Description Are you a researcher focused on thermal energy systems, sustainable industrial heating and cooling, or thermal energy storage? Are you seeking a unique opportunity to make an impact
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engineering. We aim to unravel the logic of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse
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- Collaboration with a dedicated, international team in a respected research institute - Opportunities to contribute to scientific and policy impact at the European level - A workplace that values knowledge sharing
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tools are transforming professional work. You will work with a team of leading researchers, contribute to high-impact studies, and engage with public institutions to inform real-world AI implementation
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of magnesium-based binders in different environments, with particular interest in carbonation mechanisms. You will gain hands-on experience with advanced equipment and computational modelling tools to analyse
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airborne geophysical observations, and strong competences in Arctic fieldwork logistics. The gravity research group has carried out airborne gravimetry since the 1990s and has an annual work programme to
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the wider scientific community Formal qualifications You must hold a PhD degree in chemical engineering, computer science, software engineering, data science, or a related discipline. We offer DTU is a
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: Background in Data Science, Computer Science or related fields; Working experience in implementing AI models (not just loading pre-trained model). PyTorch framework is preferred; Experience with APIs