163 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at Forschungszentrum Jülich in Germany
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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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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://go.fzj.de
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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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support and mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz
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Independent way of working Basic programming skills (Python) advantageous Very good knowledge of German or English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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data handling Strong self-initiative and willingness to learn and to quickly gain an understanding of new subject areas Joy in working independently, as well as within a team Strong problem-solving
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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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write this thesis. Interest in the field of battery development research. Very good written and spoken English; good written and spoken German desirable. Willingness to learn various electrochemical
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annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation. Where to apply Website https://www.fz-juelich.de/en/careers/jobs/2026D-017 Requirements Additional
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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