152 programming-"the"-"DAAD"-"EURAXESS"-"IMPRS-ML"-"O.P"-"Study-Group"-"Dr" positions in Switzerland
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laser processing and to bring your ideas in AI/ML to the technology level. You have a solid background in programming (deep learning, reinforcement learning, etc.), electronics, high-speed data
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experience in battery research and proficiency in Python programming is an advantage, but not a requirement. Our offer You will join a dynamic young international research group working in state-of-the-art
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scanning probe microscopy (STM or AFM), ideally with a focus on magnetic nanostructures or spin-resonance techniques Programming skills in Python or similar languages A proactive and collaborative mindset
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integration Experience with programming languages and exposure to real-time imaging analysis Strong teamwork and communication skills for interdisciplinary collaboration *Applicants who do not fully meet all
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We are supported by the Wyss Zurich Translational Center (Wyss Zürich), a unique accelerator program, which is embedded into ETH Zürich and University of Zürich and addresses the booming fields
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FAQ Short Grants Apply for Grants: FAQ Close Menu Engagement back Overview PageEngagement Awards Knowledge exchange Action plan 2025/26 back Action plan 2025/26 Empowerment GROW Guidelines & Quality
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, Robotics, or related field requirements for the position: Solid knowledge of machine learning, particularly for time series analysis and event detection Solid programming skills in C#, C++, or .NET-based
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running community programs across our industry and startup offerings, this person will be actively making things happen on the ground. You’ll help shape the future of AI entrepreneurship by translating
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computational science, computational biology, applied mathematics, physics, or a related field Strong, documented experience in C++ programming and solid software engineering skills — applicants should clearly
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biology, or applied mathematics Documented experience in C++ programming and solid software engineering fundamentals Familiarity with numerical methods for solving PDEs (e.g., finite difference, finite