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Employer
- Technical University of Munich
- BAM Bundesanstalt für Materialforschung und -prüfung
- Deutsches Elektronen-Synchrotron DESY
- Forschungszentrum Jülich
- Heidelberg University
- Helmholtz-Zentrum Hereon
- Max Planck Institute for Physics, Garching
- Saarland University
- University of Tübingen
- Universität Duisburg Essen
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Field
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies
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assets include strong programming skills, experience with modern machine-learning techniques such as neural simulation-based inference or transformer architectures, and familiarity with fitting methods and
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoctoral Researcher - Machine Learning for Plant Regulatory Genomics
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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administrative tasks. Developing proposals for projects and securing external funding Providing academic guidance to a group of early-career researchers Your profile a successfully completed PhD in physics
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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degree (M.Sc./M.Eng.) and PhD in the field of Polymer Science or comparable Experience in the field of mechanical testing or environmental stress cracking and damage mechanisms Ideally, expertise in
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to joint research activities, publications, and surveys. Requirements PhD degree (or near completion) in robotics, control, machine learning, or a related field; Strong publication record demonstrating