125 data-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" "Simons Foundation" positions at Chalmers University of Technology
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and Data Analytics, Fraunhofer-Chalmers Centre E-mail: mats.jirstrand@fcc.chalmers.se Phone: +46 730 794303 URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job
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additional tasks include to improve our main simulation tool (Atmospheric Radiative Transfer Simulator, https://www.radiativetransfer.org/ ), to apply the derived geophysical data for verifying climate models
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer. The student contributes to this project to explore fundamental and applied questions in
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and Data Analytics, Fraunhofer-Chalmers Centre E-mail: mats.jirstrand@fcc.chalmers.se Phone: +46 730 794303 Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026
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Radiative Transfer Simulator, https://www.radiativetransfer.org/ ), to apply the derived geophysical data for verifying climate models and to apply the development on the Arctic Weather Satellite and Sterna
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Join us to develop physics-guided, data-driven foundation models for multivariate time-series in safety-critical systems, with a primary focus on automotive applications. You will design predictive
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Research FieldChemistryYears of Research Experience4 - 10 Research FieldComputer scienceYears of Research Experience4 - 10 Additional Information Website for additional job details https
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Chalmers University of Technology is host for a well-funded tenure-track Assistant Professor position in Data Driven Cell and Molecular Biology, in a vibrant, international, and outward-looking work
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university hospital. Within the Division of Applied Mathematics and Statistics , research spans computational mathematics, optimisation, biomathematics, statistics, and data science, with sustained links