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-informed / simulation-aware modeling Efficient algorithms for design-space exploration (e.g., surrogate modeling, Bayesian optimization, differentiable programming) Hybrid approaches combining data-driven
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through extensive and targeted training and career programs. Compatibility of work and family life: A good work-life balance is important to our employees. Fraunhofer ISI offers flexible working hours and
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research program focused on developing next‑generation multimodal imaging systems spanning the mesoscopic to microscopic scale. As part of a major research project and supported by extensive national and
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of measurement and control technology or programming skills, preferable in python First experience with modern methods of material characterization High motivation, initiative, creativity, and ability to work in a
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opportunity to learn the process and challenges of drug discovery from the inside, including additional training and mentoring program. In addition, benefit from the rich packages for employee benefit. Our most
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degree in electrical engineering, computer engineering, computational science, or related fields Your research and development work requires knowledge of hardware-related programming and in-depth knowledge
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and Python programming skills are an advantage. Passionate about science communication and cultivating collaborative relationships with industry professionals. Excellent written and spoken English. A
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Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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datasets Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer The successful candidates will
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 2 months ago
for Galactic cartography within the framework of the Milky Way Atlas (MW-Atlas) project, an ERC-funded research program. The project is jointly led by Torsten Enßlin (MPA, Garching), Philipp Mertsch (RWTH Aachen