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development Structure–function analysis of enzymes Project coordination and team collaboration Scientific writing and publication As a formal qualification, you must hold a PhD degree (or equivalent). We offer
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analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. We strive to gain new knowledge and drive innovation in human, animal, plant and food
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academic and industrial partners in Denmark as well as abroad. We expect you to: Perform research at the highest standards Supervise BSc, MSc student and PhD students Contribute to the strong international
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-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), the Internet of Things (IoT
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, proteomics, and bioinformatics to make informed decisions on data analysis and validation experiments. Dr Francavilla’s team is funded by the Novo Nordisk Foundation and LEO Foundation and focuses
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conferences, and engaging in teaching activities. As a formal qualification, you must hold a PhD degree (or equivalent) in either electrochemistry, microbiology, fermentation, or environmental engineering, and
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cross-institutional collaboration and knowledge exchange. This project offers a unique opportunity to work at the intersection of academia, start-ups, and large-scale industry partners. Our focus is on
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of harnessing the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Centre. DTU Biosustain utilizes these advances for microbial cell
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, documented through a PhD dissertation and/or research publications experience in independently managing research projects excellent communication and interpersonal skills, with the ability to engage
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. Quantifying circular economy strategies for wind turbine rotor blades, including reuse, recycling, and feedback loops. Assessing the climate mitigation potential of circular construction materials through data