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research group, who are working on related projects. Your competencies A master's degree in chemistry or chemical engineering, materials, physics, or a closely related field. Experience with glass science
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, among others, experts with backgrounds in physics, chemistry, materials, and computer science. The section comprises four PIs and approximately 25 PhD students and postdocs. Qualifications: • Good
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at the Faculty of Social Sciences. This requires submission and acceptance of an application for the specific project to the PhD School. Please note that this process will be initiated by the PhD School only after
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are more than welcome to contact us. You will find contact person at the bottom of the jobpost. Applicants can expect interviews in September. Further information Read more about our recruitment process
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should be uploaded as ‘Resume’. All other documents should be uploaded as ‘Miscellaneous documents’. Assessment and selection process Applications will be assessed by an assessment committee. Shortlisting
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of machine learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics
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must be uploaded under ‘Miscellaneous documents’ (max 10 files with a maximum 50 MB per file). The application deadline is March 31, 2026, at 11:59 PM/23:59 (CET/CEST) Assessment and selection process
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welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here. The assessment of candidates for the position will be
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welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here. The assessment of candidates for the position will be
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institutes aims to understand how yeast cells die under industrial process conditions and use this knowledge to improve biomanufacturing. Different yeast species play a vital role in industrial biotechnology