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retreats) https://www.hds-lee.de/about/ A qualification that is highly welcome in industry 30 days of annual leave and flexible working arrangements, including partial remote work Further development of your
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Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis. You will
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on model behavior. We will divide our work into three thrusts: Thrust A: A first major objective will be to augment classical spike train analysis methods particularly those developed by Prof. Grün and
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Supervisors: https://www.fz-juelich.de/judocs 30 Days of annual leave and flexible working arrangements, including partial remote work Targeted services for international employees, e.g., through our
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retreats) https://www.hds-lee.de/about/ A qualification that is highly welcome in industry 30 days of annual leave and flexible working arrangements, including partial remote work Further development of your
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JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/judocs 30 Days of annual leave and flexible working arrangements, including partial remote work Targeted
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performance Analysis of the data to identify higher-order spike correlations and their temporal dynamics Are there particular manifold transition points and is their timing related to the occurrence of specific
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Supervisors: https://www.fz-juelich.de/judocs 30 Days of annual leave and flexible working arrangements, including partial remote work Targeted services for international employees, e.g. through our
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Your Job: We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t
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staff position within a Research Infrastructure? No Offer Description 2 Doctoral Researchers (f/m/d) in Computational and Data Science at KIT https://www.kcds.kit.edu/72.php Application deadline: January