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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
background, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference. Learn more about diversity at Helmholtz
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experimental design. Adapt, develop and learn new tools, software, and methodologies independently. Present and publish research in both academic and non-academic audiences. Attend and participate in academic
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status as a comprehensive university allows for multidisciplinary learning and teaching at JGU, in turn, paving the way for internationally renowned, interdisciplinary research. Almost all of its faculties
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
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team explores new applications of AI in collaboration with the diverse scientific disciplines associated with the Helmholtz Association. Within our lab “Applied Machine Learning”, you will play a crucial
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
advancing the state of the art in machine learning and its application to biology and medicine, with the ambition to build an internationally visible research group. The successful candidate will have the
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independently while contributing effectively within a multidisciplinary team Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be able to teach you
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on the applications of logical zonotopes in digital circuits and the model checking of discrete-space systems, with the goal of developing methodologies and tools that make verification scalable and reliable. Learn