23 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions at Forschungszentrum Jülich in Germany
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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-time ( https://go.fzj.de/near-full-time ), allow you to customize your working hours. VACATION: You will receive 30 days of holiday plus free bridge days (e.g., between Christmas and New Year). FAIR
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closely linked to a related opening at IMD-1 at Forschungszentrum Jülich within the same project consortium: https://www.fz-juelich.de/en/careers/jobs/2025-361 Please feel free to apply for both available
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-scale research facilities (e.g. DESY, ESRF), including coordination and setup of experiments Development of data workflows and analysis strategies (in collaboration with our machine learning team
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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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models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs FAIR REMUNERATION: Depending on your existing
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addition to exciting tasks and a collaborative working atmosphere at Jülich, we have a lot more to offer: https://go.fzj.de/benefits We offer you an exciting and varied role in an international and interdisciplinary
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to industry partners to learn and set up on-site research Preparing scientific publications and project reports Your Profile: Strong motivation for an interdisciplinary project that combines physics and biology
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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis