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project is to uncover how collective dynamics and signal-ing feedbacks drive robust pattern formation during early development. We apply advanced stem cell culture approaches, 3D organoid engineering, and
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, or dynamic transmission models) to assess their potential health and economic impact (incl scenario and uncertainty analysis Use experimental, clinical and programmatic datasets for model parameterisation
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sounding systems Basic knowledge on middle atmosphere dynamics and spectroscopic methods Fundamental programming skills in, e.g., Python, Julia, C/C++. Expertise in automatic data processing and handling
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. The position provides excellent career development opportunities within a dynamic, interdisciplinary and highly collaborative research ecosystem spanning LMU Klinikum, LMU, the SyNergy Cluster of Excellence, and
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provide a dynamic environment which empowers excellence with state-of-the-art technologies, cutting edge infrastructure, and a global scientific network. Contribute your knowledge, vision, and dedication
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
into high-impact publications and patents Commitment to working in a fast-moving and highly competitive field as well as in a dynamic and highly collaborative group Excellent written and spoken
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across the lifespan, with a particular emphasis on ecological active learning—how learners interact dynamically with their environments to acquire knowledge and make decisions. This is an open-topic
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We Offer A highly dynamic and interdisciplinary research environment at one of Europe’s top technical universities Access to state-of-the-art robotics labs and collaborative projects with leading
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autonomy. ✅ High interest in cultural heritage applications. ________________________________________ Our Offer • Dynamic and interdisciplinary research environment bridging heritage science, materials
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language, e.g. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Dynamical