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-doctoral candidate with experience in numerical modelling, preparation and experimental characterization of nanostructured materials to join our SNSF project “Coupled oscillations in plasmonic
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SU-2-1 Futureproof energy and materials feedstock resilience for sustainable aviation fuels supply chain Green Industrial Futures Centre for Doctoral Training (GIF CDT) PhD Research Project Directly
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localities and will use that data in geochemical and geophysical numerical modelling. The team will work on three main tasks: Improve the accuracy of plume source composition Quantify changes with tectonic
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exciting research program within the Foy Lab ( www.foylab.xyz/ ) https://foylab.xyz/ , developing machine learning, computational, and mathematical models for improving how clinical blood tests are used
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areas: Blue/Green Infrastructure: restoring, managing and protecting nature-based assets in urban and rural environments Sustainable Materials and Resources: developing materials and technologies
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Geological Survey of Denmark and Greenland (GEUS) | Copenhagen, New York | United States | about 1 month ago
Quaternary geology with regional 3D geological modelling and help connect Denmark’s onshore and offshore subsurface? Are you motivated by using geological knowledge to address some of the major challenges
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Development of Thin Films and Deposition Processes using Artificial Intelligence and Autonomous Experiments. Share Apply now Materials science and technology are our passion. With our cutting
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) You will work within the newly established Computational Materials Science group of Assistant Professor Waldemar Kaiser, part of the Theory & Modelling unit (led by Prof. Igor Zozoulenko). Our
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successful candidate will work on can be found on the SPRING project website https://spring-project.eu/doctoral-projects (position reference DC 12). SPRING DN is implemented by an international consortium
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observation systems, and integrated analysis and modelling approaches. The position focuses on holistic catchment-scale studies and the development of scalable methods for monitoring the state, changes