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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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of Civil and Mechanical Engineering, Thermal Energy Section. We look for a talented, self-motivated, and team-oriented individual who thrives in a collaborative environment and enjoys tackling complex topics
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environmental engineering. A collaborative and analytical mindset, with the ability to synthesize complex information across experimental and theoretical domains. Enthusiasm for advanced electron microscopy
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. Responsibilities and qualifications Qualifications: PhD degree in Engineering, Physics, Computer Science, or Applied Mathematics. Proficiency in scientific programming with Python. Excellent oral and written
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and machine learning, you will help develop new methods for understanding complex failure mechanisms—an area where existing industrial knowledge remains limited. The project will be executed in three