82 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at Chalmers University of Technology
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: Develop advanced computational models, including mechanistic enzyme-constrained models (ecGEMs) for Y. lipolytica and D. hansenii, integrating RCD pathways. Leverage cutting-edge data from experiments and
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Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteChalmers University of TechnologyCountrySwedenCityGothenburgPostal
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materials. The first position will focus on developing novel representations for polymers, both for more data efficient polymer property prediction and polymer generation, and the second position will focus
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- integrating PET/CT images, radiology reports, and clinical data - to develop more accurate and trustworthy diagnostic tools. You will join a dynamic, interdisciplinary research group with extensive
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the Division of Data Science and Artificial Intelligence . About the research project This PhD project explores multi-agent decision making from the perspective of Markov Decision Processes (MDPs). MDPs are a
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Initiative for gender equality and excellence . If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers
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activities. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers here . Application procedure
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aspects of all our activities. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers here
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announcement publishing or other types of support for the recruiting process in connection with this position. *** URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job
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. The project integrates physical ship performance models with operational data and offers a unique opportunity to contribute to sustainable shipping by improving the efficiency and automation of wind-assisted