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Partnerinserat Übersicht ETH AI Center Post-Doc Fellowship 2027 100%, Zurich, fixed-term Drucken The ETH AI Center promotes trustworthy, accessible, and inclusive AI systems. For this goal, we
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related questions in an interdisciplinary manner (i.e., at the intersection of psychology, technology, and human–computer interaction). We welcome candidates with a strong interest in fundamental
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Electrical Engineering Mechanical Engineering Physics Neuroscience Computer Science Chemistry or a closely related field Ideal candidates should possess several of the following: Excellent academic
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, and synthetic materials, actuated by muscle and powered by chemical energy. Perception and Computer Vision: 3D reconstruction, object recognition, and scene understanding that give robots reliable
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benchmarks Debug common post-training issues, including optimisation instability, reward hacking, regressions, and evaluation failures Profile Essential MSc or PhD in Computer Science, Data Science
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quantitative and analytical skills, incl. programming (Python, MATLAB, or similar) Experimental laboratory experience in drug formulation, nanoparticle/microbubble synthesis, colloid chemistry, or related
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, modular, and reusable scientific code (primarily in Python) following modern development practices, including version control (Git), automated testing, code style/linting, and clear technical
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modulation Software development for optical modeling and numerical analysis (Python, MATLAB, or equivalent) Strong academic output relative to career stage, evidenced by high-quality publications or
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analysis, and multi-modal integration is a strong asset (e.g, connectivity analysis). A proven track-record in current flow modeling (SIMNIBS) for TMS and/or tDCS. Skilled in programming (Python, MATLAB, R
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skills are an advantage Solid R and/or Python skills, ideally paired with modern AI-assisted coding workflows (e.g., Claude Code), are a clear advantage Track record of first-author publications Excellent