147 systems-science "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich
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which everyone can realize their potential is important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and and on the targeted
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“Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. The position is placed at the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum
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addition to exciting tasks and the collaborative working atmosphere at Forschungszentrum Jülich, we have a lot more to offer ( https://www.fz-juelich.de/en/careers/julich-as-an-employer/benefits ). The position is for
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located: https://www.fz-juelich.de/en/pgi/pgi-7/research-groups-1/ag-gunkel-1 Your Profile: Completed qualification to enroll for the Master thesis in Physics, Chemistry, or Materials Sciences, with a good
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
limited to 2 years with possible long-term prospect CAREER CENTER: You will receive explicit support with regard to your career development opportunities: https://go.fzj.de/careercenter In
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, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a
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related field Great interest in energy technology, energy economics and policy issues Experience in programming with Python or a comparable programming language Experience in energy system modelling is an
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14 Mar 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 30 Apr 2026 - 22:00 (UTC) Country
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establishing the institute`s research infrastructure and laboratory operations Your Profile: Bachelor or Master`s degree in physics, electrical engineering, control systems engineering, mechatronics, or a
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time