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Field
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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proficiency in Python and experience with ML/DL frameworks like PyTorch or TensorFlow Strong analytical and communication skills, creativity, and the ability to work independently while collaborating in a team
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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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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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Python Independent and analytical way of working Reliable and thorough working style Fluent written and spoken English; German language skills are advantageous Please feel free to apply for the position
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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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; 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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, catalysis studies - in particular electrocatalysis and Python programming Experience within the following fields is highly beneficial: Transmission electron microscopy, Electrochemistry, Image analysis, Big
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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