80 structures-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" scholarships at Forschungszentrum Jülich
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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on the campus of Forschungszentrum Jülich. Your tasks include in detail: Construction and commissioning of a new test stand for the investigation of the continuous butanediol dehydrogenation under dynamic
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population-level neural interactions. Prior work has emphasized rate-based codes due to their relative simplicity; our approach will explicitly extend these models to capture temporal structure within spike
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) conferences Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in industry Further
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: It is important to us that you quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome
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data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ 30 days of annual leave (depending on agreed working time arrangements) and provision for days off between
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development, stack construction, system and component development, microscopy, spectroscopy) Presentation of findings at specialist conferences, publication in leading journals and active exchange with industry
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structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de
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partner is possible Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in
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explicitly extend these models to capture temporal structure within spike trains thereby moving towards analyses that are sensitive not just to firing rates but also precise timing relationships underpinning