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the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting date is 1 Januar 2026, with
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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. The Department of Mathematics and Computer Science, Hessain.AI research group “Artificial Intelligence – Deep Decision Support Systems”, led by Prof. Dr. Martin Becker, is currently accepting applications for a
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mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and experience with the Linux operating system
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closely with the Department of Mathematics at Aarhus University. In addition, your organic chemistry skills will be instrumental in developing antioxidant artificial cells. These interdisciplinary projects
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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interdisciplinary, and together we contribute to science and society. Your role The successful candidate will join the Enzymology & Metabolism group, led by Prof. Carole Linster, which deciphers the cellular
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort