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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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); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC Starting Grant ArtDisQ and the
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performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under
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. The candidate will also collaborate with the Department of Computer Science at Kiel University and the remote sensing company EOMAP GmbH, employing state-of-the-art machine learning techniques to improve
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-driven energy systems research – scalable, transparent, and interoperable. Your tasks in detail: Development of a structured description format for the unambiguous and machine-readable characterization
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[maps] and the TUM Garching campus [maps], and all members are affiliated with both institutes. As a PhD candidate in our group, you will drive your own research on machine learning methods in close
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr
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science (for example, but not limited to, data science, machine learning, statistics, computer science, mathematics, etc.) acceptance by a PhD supervisor with examination admission for PDS and formation