74 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at Technical University of Denmark
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the project. Your main tasks will be: Develop and apply electromagnetic modelling techniques in combination with inverse design to study light-matter interactions in dielectric nanostructured optical surfaces
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. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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. Candidates with diverse backgrounds in stellar modeling and those who have worked on various types of stars are encouraged to apply. As a formal qualification, you must hold a PhD degree (or equivalent). We
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. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus
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involve the following tasks: Supervision of BSc/MSc and PhD students related to the project. Performing catalytic tests on upgrading pyrolysis oil and pyrolysis oil model compounds using an advanced
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properties You will work in close collaboration with a group of senior scientists, technicians as well as postdocs and PhD students. Also, the work will involve collaboration with selected external partners
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potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat transfer and
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this postdoc position, along with an additional postdoc and one PhD position, we will tackle this grand challenge by fabricating and studying electrocatalysts with three-dimensional active site structures. With
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, protocols, and data standards across collaborating institutions and scales. This collaboration will support the generation of coherent, high-quality datasets and enable the development of predictive models