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, supervise junior researchers and students, and contribute to teaching activities in AI and data science for medicine Your Profile PhD in Artificial Intelligence, Computer Science, Data Science, Computational
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. Work on other ATLAS physics topics may also be considered depending on the candidate’s expertise. A PhD in particle physics and substantial experience in data analysis are required. Additional valuable
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research in the natural, mathematical and computer sciences with a focus on the processing, structuring, and analyzing of large amounts of complex data and the development of computational methods and
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Science in Earth Observation develops innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth
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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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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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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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Integration group led by Dr. Jędrzej Szymański. Our group specializes in machine learning, multi-omics data integration, and the development of predictive models for plant gene regulation. We are part of
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, particularly in the field of element-specific investigation of functional magnetic materials at large research facilities. In addition, you will be involved in the implementation and execution of courses and
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Helmholtz Association of German Research Centres | Oldenburg Oldenburg, Niedersachsen | Germany | 3 months ago
research. The project will combine established methods from historical research with modern approaches from machine learning and network science. Your TasksThe work will involve the analysis of historical