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procedure. Develop Python-based image-processing and annotation workflows and train and evaluate segmentation models for the automated detection and quantification of relevant visual features. Profile
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physical platform; components are designed for reuse across all deployment contexts Python backend development, with a focus on LLM integration such as improving dialogue quality, story adherence
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partners Provide organizational support to the group head Profile A PhD in engineering with a focus on industrial applications A proven track record in AI and strong proficiency in Python At least 3
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, LSTMs) with applications in industry. Knowledge/courses taken on estimation theory, network modeling, and graph theory are a plus. Excellent coding skills in python, ROS, and ML pipeline experience on
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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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drawing, spatial representation, and chair culture Genuine curiosity about AI tools and digital methods in an architectural context Experience with Python programming, modern web development and AI
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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
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-Headsets. 3D-Software: Sehr gute Kenntnisse in Rhino; Erfahrung mit BIM-Software (Revit/ArchiCAD) zur Datenübernahme ist von grossem Vorteil. Programmierbezug: Grundkenntnisse in Python oder