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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
findings at academic venues and publish research in peer-reviewed journals Your profile # Completed university studies (PhD) in the field of Physics, Computer science, Materials science, Chemistry, or a
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The Max Planck – University of Helsinki Center for Social Inequalities in Population Health is currently seeking to appoint one or more full-time post-doctoral researchers. We welcome applications
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Postdoc (f/m/d) Computational Ecologist/Species Distribution Modeller / Completed university stud...
journals Your profile # Completed university studies (PhD) in the field of Biostatistics, Ecology, Biology, Geo-ecology, Geography, Mathematics or related field # Relevant professional experience in
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Postdoc (f/m/d) Research Data Management and Data Visualization / Completed university studies (P...
scientific papers, representation and presentation of the project, project reporting Your profile # Completed university studies (PhD) in the field of Computer Science or a matching application area with a
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the programme as a tandem Academic Requirements Predocs: graduates (Master's, Diploma or State Examination) from a German or international university in the transition phase at the end of their university studies
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agri-food value chains and on providing methodological guidance (co-creation and collective intelligence methods) for promoting the development of new Agroecology Living Labs. Your tasks: Conducting
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scientists from all areas of the natural sciences, medicine, the history of sciences or any other disciplines covered by sections of the Academy are eligible to apply. Applications can be submitted up to 7
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for physics and materials science applications scenarios as well as for related research data management tasks Developing LLM-driven agents that integrate domain knowledge to support structured chain-of-thought
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design of P2X value chains. In this versatile and future-oriented postdoctoral position, you will play a key role in the characterization of novel high-temperature electrolysis stacks (Solid Oxide
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Correct), Bayesian statistics, systems theory and artificial intelligence are to be used as a basis in order to explore and implement a continuous calculation chain starting from observable and controllable