29 analytic-number-theory Postdoctoral research jobs at Technical University of Denmark in Denmark
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in district heating modelling, advanced controller development, and smart energy systems is advantageous. Strong analytical skills, the ability to work collaboratively in interdisciplinary teams, and a
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are planned to improve the understanding of cross-shore transport of microplastic particles. You will be leading these to campaigns. Additionally, you will lead the development of simple models for cross-shore
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qualifications The exact research focus will be shaped in dialogue with the successful candidate, depending on their expertise and interests. You are expected to be an independent researcher and take the lead on
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and colorimetry assays Analytical chemestry Microscopy Previous experience with Food science and nutritional science We expect that you are an efficient team worker, have good communication skills, and
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candidate with a strong background in semantic data modeling and knowledge representation, ideally in engineering or scientific domains. You will take the lead in designing, extending, and implementing
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academic network. Responsibilities You will co-lead the development of advanced thermal systems for industrial decarbonization; you will be responsible of development of advanced thermal systems
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scientific challenge and also has clear application perspectives. The department has a number of state-of-the-art research facilities, including a supercomputer. Furthermore, the Department of Physics
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from previous campaigns and new data collected through upcoming fieldwork. You are expected to: Lead the preparation and submission of scientific manuscripts for peer-reviewed (ISI) Present your findings
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are required for the new generation of anti-fouling coatings. Anti-corrosive coatings Corrosion can lead to structure failures that have dramatic consequences for humans and surrounding environments. The use
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these to campaigns. Additionally, you will lead the development of simple models for cross-shore sediment transport predictions. These models will be based on an extensive experimental database containing historical