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. The position is embedded in the collaborative research program “Precision Organoid Engineering for Multi-Organ Interaction Studies (POEM)”: www.uni-heidelberg.de/en/cctp-poem The POEM program aims to generate
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side projects and build networks inside and outside the institute Analyze diverse data sets for multi-omics integration in plant genetics Expand expertise and collaborations beyond plant research Our Lab
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English Your experience should be documented in research papers and Open Source code projects Self-motivated personality, curiosity about working in a multi-disciplinary team environment on scientifically
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at the Berlin institutions of the Prussian Cultural Heritage Foundation (SPK). Funding is available for research projects, if they are related to the multi-faceted institutions of the Foundation. The programme
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of Livestock Systems is newly established at TUM and will include several postdocs, PhD students, and technical staff. The team will work on various topics, including multi-scale analyses of productivity
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electrochemical gas sensor (PEGS) based on fast Li-ion conductors. The fast ion-conduction characteristics of Li-based materials unlock the possibilities of cost-effective, low-power, multi-sensing arrays with a
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at TUM and will include several postdocs, PhD students, and technical staff. The team will work on various topics, including multi-scale analyses of productivity, nutrient and water cycling in livestock
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of psychology (in human-robot interaction) and communications (in networked control systems). Many of the developed methods are experimentally validated in our multi-robot lab. Your qualifications: We
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, climate and earth system modeling, soil parameter mapping, and multi-sensor segmentation, together with our partners at renowned international and national institutes such as Bonn University, Alfred Wegener
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Carlo, multi-phase field models and similar • Preferably knowledge in welding and additive manufacturing • Preferably knowledge in data-driven methods in materials science • Interest in project management