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research. We are looking for an enthusiastic researcher who is quick to grasp new concepts and ideas and can solve complex deep learning problems with high-quality software solutions. Experience with large
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to different domains. Specifically, you will: Develop, implement, and refine Machine Learning (ML) techniques for self-supervised Deep Learning (DL) for scientific and large-scale datasets Implement parallel ML
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to identify degrading enzymes from different data resources Using Hidden Markov Models and similar tools as well as machine learning for the identification of novel and better enzyme variants from a
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career opportunities supported by our Career Center & Postdoc Office ( www.fz-juelich.de/en/career-center-postdoc-office ) Targeted services for international employees, e.g. through our International
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Exploration and preparation of next career opportunities supported by our Career Center & Postdoc Office ( https://www.fz-juelich.de/en/career-center-postdoc-office ) Targeted services for international
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on the atomic and mesoscopic scale using neutron methods, complementary X-ray experiments and support of further techniques including computer simulations Synthesis and physicochemical characterization of energy
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the efficient and reliable analysis and interpretation of different experimental imaging techniques such as atomic force or electron microscopy as well as tomography. We intend to use different machine learning
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on large scales Strong programming skills, preferably in C++ Some knowledge of Fortran, Python and Julia is an asset Some background knowledge in Machine and deep Learning is an asset A self-motivated