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Field
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in the areas of statistical methods for high-dimensional and/or large-scale data, mathematical and statistical foundations of machine learning, statistics of stochastic processes and dependent data
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Integration group led by Dr. Jędrzej Szymański. Our group specializes in machine learning, multi-omics data integration, and the development of predictive models for plant gene regulation. We are part of
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
and advance statistical, image analysis, and machine learning approaches Develop interpretable models that reveal biologically testable relationships and generate new scientific hypotheses Independently
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European Molecular Biology Laboratory (EMBL) | Brandenburg an der Havel, Brandenburg | Germany | about 2 months ago
machine learning/AI with modern biology at the AI Hub Heidelberg as part of EMBL AI, a major institutional initiative to embed AI across all areas of life sciences. EMBL provides a unique environment for
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
analysis, image analysis, statistical, and machine learning methods, choosing the approach that best fits the scientific question. Investigate systematically what information is contained in imaging data
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-based methodologies for protein structure prediction and cofolding Machine learning guided virtual screening Taking on organizational tasks and writing grant applications Your Profile The ideal
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Rheinische Friedrich-Wilhelms-Universität | Bonn, Nordrhein Westfalen | Germany | about 2 months ago
techniques from robotics, machine learning, plant phenotyping, and modeling. These technologies lead to new opportunities for field management, plant breeding, or sustainable crop production. The professorship
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and (on-site) appointments Vacation: You will receive 30 days of vacation plus additional days off (e.g. between Christmas and New Year's) Flexibility: Flexible working time models, including options
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datasets for training a machine learning model • Development of ML-based spatio-temporal interpolation methods • Geophysical interpretation and analysis of the results and impact assessment of past and