157 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at Forschungszentrum Jülich
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en
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development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs FAIR
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opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs HEALTH & WELL-BEING: Your health is important to us. You can look forward to a comprehensive company health management
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https://go.fzj.de/welcome WORK-LIFE BALANCE: We offer
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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 Days and Welcome Guide: https
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energy system models based on the institute`s own open-source FINE framework https://github.com/FZJ-IEK3-VSA/FINE. Your tasks in detail: Implementing geothermal plants with material co-production in
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: Your professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https
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international project partners, embedded in an ERC-funded project. For deeper insights, please have a look at our institute website: https://www.fz-juelich.de/en/pgi/pgi-7 and the research group in which