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Field
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machine learning (ML), artificial intelligence (AI) or related fields • Software skills in ML languages such as Python • Ability and enthusiasm to learn new technologies quickly • Ability to work highly
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data analyses includes writing well-documented, reusable code (Fortran, Python or R) Collaborate closely with fellow PhDs and project partners in an interdisciplinary context Present, publish and
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or for multiobjective optimization problems. Implement the developed algorithms (e.g., in Python) and evaluate their practical performance on artificial and/or real-world data. Teach tutorials (in English) for
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coding skills, particularly in Python and machine learning frameworks (PyTorch or Jax) The ability for creative and analytical thinking across discipline boundaries and abstraction levels Knowledge in
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the solid Earth and ice sheets Excellent problem-solving skills and ability to creatively apply multidisciplinary knowledge Excellent command of scripting and programming languages like shell, Python or C
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; Experience with HPC, programming (e.g., Python, C/C++), and/or scientific computing is a plus Strong interest in quantum computing and molecular simulations Willingness to work in an interdisciplinary
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, physics, or similar, with a strong Machine Learning or simulation background In depth practical experience in at least one programming language (preferably Python) Ideally, some practical experience in
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or more languages (Matlab, Python, R, C, Fortran) excellent knowledge of English (written and spoken) high degree of motivation, creativity, and flexibility ability and willingness to participate in sea
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of seismic methods and numerical simulations, Good PC and programming skills (e.g., with Python, MATLAB), Experience with measurement techniques and field measurements using sensor technology (ideally using
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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