49 machine-learning "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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, machine learning, energy technology or related subjects Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression Experience in
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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the collected data in accordance with FAIR standards for collaborative use within the Decode project and for machine learning applications Presentation of results in team meetings and preparation of a
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. Usadel, specializes in data integration, classical bioinformatics, data science, and machine learning. The offered position will focus on the ELN-RO project, which has the aim to establish seamless
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skills (Python, R, Java, …) and interest to work in polyglot software environments Practical experience with machine learning and AI methods and an interest to learn, adapt and apply ML methods
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) Intense interaction with consortium Your Profile: Master and PhD degree in materials science, physics, chemistry, informatics, machine learning, energy technology or related subjects Prior experience in
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Your Job: Investigate current challenges and bottlenecks in power flow analysis for large scale electrical distribution grids Apply machine learning/AI or surrogate modeling (e.g., neural networks
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institute Supervision from both chemical engineering and machine learning experts, ensuring strong interdisciplinary guidance Your Profile: Current Master`s student in Process Systems Engineering
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Your Job: In this position, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting