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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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, machine learning or causal inference for estimating, understanding and forecasting demographic and health outcomes, at the individual and aggregate levels, including as they relate to life course and socio
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student assistants and contribute to shaping the CRC’s research direction Your Profile PhD in computer science, neuroscience, machine learning, or related field Strong programming skills in Python and
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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19.07.2022, Wissenschaftliches Personal The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current