57 postdoc-in-thermal-network-of-the-physical-building PhD positions at Technical University of Munich
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have a strong interest in process-oriented research in plant physiology/plant ecology. Practical experience in field work, statistical data analysis (R), knowledge of German and a driver's licence are
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a defined research topic to deriving an improved process understanding and communicating the results. Ideally, the applicant should have some background in (soil) incubation experiments and advanced
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scale Research budget for conference attendance and professional development. Opportunities to collaborate with leading industry partners. Access to world-class academic resources. Application Process
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collaboration, we aim to promote biodiversity-based health interventions. The research is funded by the Research Initiative for the Conservation of Biodiversity (FEdA), the Federal Ministry of Education and
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architectures which leverage our increasing understanding of the behaviour of neural networks trained with DP to ameliorate these trade-offs in biomedical applications. - Foundations of private machine learning
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deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. We are seeking a researcher to join our team in an ERC project on DNA data storage
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/CAROUSEL) and its application for developing new materials and adapting the additive manufacturing process parameters, we are looking for support as soon as possible. The Chair of Materials Engineering of
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) for performing fundamental research in the frame of the project DrawOn funded by the Bavarian State Ministry for Economic Affairs, Regional Development and Energy. The candidate has the opportunity to pursue a
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personal profile, potential tasks include but are not limited to: - Development of a recirculation system for culture medium in a perfusion bioreactor system - Implementation of process control, soft sensor
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TEA of a defined process for cultivated meat with material cycling - Optimize the process, also applying mathematic modeling, to improve yield and sustainability - Independent work on research projects