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conversion reactions. The second position is focused on modelling stability of electrocatalyst materials. The aim is to develop a framework to predict metastability of catalyst materials. Among the methods
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offer Joining our team will provide you with numerous benefits, including: The opportunity to explore completely new regimes of physics and information, both theoretically and experimentally
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teamwork with other local consortium members in the capital region of Denmark and with parallel international collaborators in the UK. In addition, collaboration with other NIVI-R human challenge sites will
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well as abroad. To support your success, you will have access to DTU National Food Institute’s excellent laboratory facilities. Your overall focus will be to assess if the current biocide assessment methods based
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(particularly for packaging), and analytical techniques Experience in packaging processing technologies (e.g. extrusion, Injection, compression molding, others) Familiarity with relevant methods such as
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application phases. This will involve toxicological testing (e.g., cytotoxicity, mutagenicity) and evaluating microplastic release and ecotoxicity using standardized and novel methods (in collaboration with a
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Policy Implications and Recommendations Case Studies of Successful Innovation Funding Methods The project will employ a combination of methods, including machine learning (ML) and generative AI (GenAI
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doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design
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theoretical and computational work in topological photonics and nanophotonics. Day-to-day project activities will include numerical computation and theoretical analysis of the photonic properties of candidate
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and