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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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distinguished record of research leadership in higher education. Expertise in navigating complex funding systems, innovation ecosystems, and global research trends. Exceptional communication skills and the
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real-world solutions and contribute to a sustainable future. Building upon a strong foundation in core engineering and scientific principles, the M.Tech. program delves into the complexities of renewable
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and international network structure in order to integrate existing competences and knowledge, and to link various actors within the complex area of climate change. This 3-year position, part of
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, Heidelberg and Mannheim, our researchers harness interdisciplinary collaboration to decipher the complexities of disease at the systems level – from molecules and cells to organs and the entire organism
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]. The complexity of these issues is amplified in the FL setting, where each participant has only access to its own data. Candidate profile: The candidate should have a solid mathematical background (in particular
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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. You will have ample opportunity to work with highly complex research datasets in the areas of population genetics and genomics, epigenomics (Karadimitris, Crump, Feldhahn, Agrawal Singh, Chaidos
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complex device preparation (e.g., de-lidding or thinning), the capability to irradiate whole systems at once, as well as improvements to the efficiency of space relevant radiobiological experiments. GSI
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Institute for Meteorology. YOUR PROFILE We are looking for a curiosity-driven and conceptually-minded candidate who enjoys scientific discussion and complex data analysis. To be considered for this position