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, and energy systems into a comprehensive bio-based circular economy. We develop and integrate techniques, processes, and management strategies, effectively converging technologies to intelligently
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at large scale facilities Establishment of cooperation projects with energy-related institutes at Forschungszentrum Jülich Initiating grant applications Supervision of MSc and BSc students Presentation
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team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You
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Your Job: You will develop impactful machine learning techniques to deal with complex quantum states. Possible research directions and tasks include: Method development to advance neural quantum
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well as the opportunity to design and construct instruments and/or sample environments Establishment of cooperation projects with institutes at Forschungszentrum Jülich working on energy materials Supervision of MSc and
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control and optimization of electrolysis from the cell to the stack requires automated monitoring, analysis, and control of the operating parameters and processes. As part of this project, the potential
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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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harbouring excellent research and education provide patient care at the highest medical level with around 11.000 employees. The Klinik und Poliklinik für Radiologie (Department of Radiology) on the Campus
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, the model will maintain a global scope to capture international interactions, such as the demand for agricultural products from regions like the EU. This research will inform the design of effective and
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the study of the impact of digital and computational pathology on clinical workflows and patient care. Our lab is located in the heart of Munich at the TUM Klinikum rechts der Isar (MRI), Institute