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for competitive fellowships during their first year with us. The ideal candidate will be recruited by summer 2025. We are particularly seeking postdoc candidates who have recently completed their PhD with a
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, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns
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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 successful candidate will develop computational approaches to discover, model, and develop therapeutic strategies. Examples of potential approaches include: -Network Modeling: Creating
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well as computational modeling. The development and numerical implementation of novel methods has become a key issue in modern oncology, both in terms of understanding the biology of cancers and for medical oncology
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the exact calculation of the square-root and inverse square-root of the source distribution covariance matrix. This approach offers analytical and computational advantages in comparison to existing methods
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close as possible to tumor sites to deliver its high-energy radioactive radiation, allowing the destruction of targeted the cells. Research program: Belonging to the halogen series, astatine exhibits in
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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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: 305,000 euros total funding over the project duration, including: • 199,000 euros for contractual collaborators (PhD students, postdocs, research assistants) • 106,000 euros for operational expenses
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to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological