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Infrastructure resilience under multi-hazard scenarios Model development and data analyses includes writing well-documented, reusable code (Python or R) Collaborate closely with fellow PhDs and project partners in
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practical experience in at least one programming language (preferably Python) Ideally, some practical experience in material characterization methods Structured and analytical thinking as well as a systematic
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language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g., Git) Interest in or experience with semantic web
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microscopy data is an asset but not required Interest in foundational machine learning research with applied impact in scientific imaging Demonstrated proficiency in Python and experience with ML/DL frameworks
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Engineering, or related fields. Solid background in structural dynamics, wind engineering, and finite element modelling. Experience in programming (MATLAB/Python) and/or structural analysis software (e.g
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/or interest in programming languages (e.g. MATLAB, Python, R) and software platforms such as Autodesk, ALLPLAN, ANSYS, REVIT, Tekla, Rhino, Grasshopper, etc. Basic knowledge in the areas of signal