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automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism, mutual
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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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. Through academic, clinical, and industry partnerships, as well as global networks, we strive to translate biological discoveries into applications that enable the early detection of deviations from health
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. Göttingen as a city of science is located in the center of Germany and the University Medical Center Göttingen is integrated into an attractive network of university and non-university scientific institutions
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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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#an exciting and varied job in a research centre with around 1,000 employees from more than 60 nations #a well-connected research campus (public transport bus) and best networking opportunities #individual
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genomic, gene expression and gene regulatory network data sets. We are looking for a highly motivated scientist to work in a dynamic and interdisciplinary academic team focusing on different aspects
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competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven German Universities of Excellence and provides outstanding working, research, and networking possibilities