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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning
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spoken and written English Our offer A vibrant research community in an open, diverse and international work environment Scientific excellence and extensive professional networking opportunities A
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and international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking
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Equity Fields of Action Networks for Equity Kontakt Team Equity News and publications Back Press Releases attempto online Newsletter Uni Tübingen aktuell University of Tübingen magazine Attempto
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Project summary: A transition to net zero is desirable overall, but its costs and benefits are unevenly distributed across time, space, and between individuals, and policy to implement it must be
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sciences a pleasant and respectful working atmosphere integration into a successful and committed team in an international environment and network flexible and family-friendly working time models and the
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Qualified supervision by scientific colleagues Independent preparation and implementation of the assigned tasks A large research campus in the countryside, which offers the best opportunities for networking
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for horticultural sciences a pleasant and respectful working atmosphere integration into a successful and committed team in an international environment and network flexible and family-friendly working