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elasticity, dissipation, and slender geometry interact to influence crack initiation and growth. Using in-house codes and high-performance computing resources, the candidate will simulate fracture processes
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-constrained Machine Learning, and the match with the eDIAMOND project’s goals. For example, you can mention: Your achievements and awards (e.g., participation to coding competitions, olympiads in math
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technical AI experience and research interests Bachelor's and Master's transcripts and diplomas Code samples or links to GitHub repositories (if available) Applications should be submitted through the ETH
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computational methods Coding abilities in at least one language Excellent proficiency in English as working language Good soft skills for independent work and team-work A keen interest in molecular modelling, in
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Excellent coding abilities in at least one language Knowledge and experience with fracture mechanics and/or phase-field modeling are a plus A keen interest in computational mechanics and in scientific methods
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to analyze crystallographic data and model electronic structures in complex materials. The work involves creating code for processing diffuse scattering data, performing density functional theory (DFT
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research, or forestry during your coursework, you're already on the right track! Programming Enthusiasm: You enjoy solving problems through coding and have some experience with R or Python for data analysis