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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 13 hours ago
) in Geometric Deep Learning to join the Machine Learning and Artificial Intelligence (MLI) g roup to perform research in geometric deep learning for materials science. This research is part of
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important roles: data management and engineering, machine learning and data analytics, signal and image processing, algorithm design, optimisation and simulation, software engineering and automation and
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Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being excited to make a real impact with
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are interested in combining disciplinary knowledge with the skills of a data scientist and working at the interface of bioinformatics, medical informatics, databases, data mining, machine learning, applied
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individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal of understanding biological systems in their entirety. The study of biomolecular systems poses
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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Strong Python programming skills and familiarity with machine-learning frameworks (e.g., PyTorch), data engineering, SQL and version control Interest in longitudinal clinical data, clinical terminologies
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RPTU University Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 4 hours ago
tailored to their needs. For further information, see: https://www.physik.uni-kl.de/oscar/ . Course organisation During the research work, the PhD student has the possibility to participate in lectures which
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concepts about biological processes, advance information technologies and human-machine interactions and, last but not least, provide new insight for designing efficient strategies for teaching and learning
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts