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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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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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genomic data using deep learning methods in order to identify degrading enzymes from different data resources Using Hidden Markov Models and similar tools as well as machine learning for the identification
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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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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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interpretation of different experimental imaging techniques such as atomic force or electron microscopy as well as tomography. We intend to use different machine learning (ML) algorithms with a strong focus on
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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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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