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to the FAIR-ification of data, establishing systematic data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s
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Your Job: You will strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists
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for an enthusiastic researcher who is quick to grasp new concepts and ideas and can solve complex problems with high-quality software solutions. You will work with machine learning, HPC, and domain science experts and
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Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant applications, e.g
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Your Job: You will join the Simulation and Data Lab `AI and Machine Learning for Remote Sensing`, which aims to enhance visibility in interdisciplinary research between applications from remote
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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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disciplines with PhD Extensive knowledge of machine learning/artificial intelligence and big data science Extensive knowledge of programming languages (ideally Python) Basic knowledge of synchrotron research
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dynamics of energy materials on the atomic and mesoscopic scale using neutron methods, complementary X-ray experiments and support of further techniques including computer simulations Synthesis and
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, free energy calculations, machine learning/deep learning, Markov State Models, docking Your Profile: Master degree in the field of Biology/Physics/Chemistry or related High motivation and interest and/or
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Your Job: In this position, you will be an active part of our Simulation and Data Lab Applied Machine learning. In national and European projects, you will develop new, innovative applications