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! Education · PhD in computer science, engineering, applied mathematics, physics, or another STEM discipline. · Demonstrated experience with mathematical and numerical optimization methods
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if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or
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, Computational Science, Physics, Engineering, or a closely related discipline Strong background in differential equations and numerical methods Solid programming skills e.g. Python, C++, Julia or similar Interest
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ML frameworks like PyTorch/JAX Genuine interest in MLFFs, simulation methods, and foundational ML research Desired skills: Experience with atomistic simulation codes: ASE, FHI-aims, VASP, CP2K