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02.07.2025, Wissenschaftliches Personal The Professorship of Energy Management Technologies at TUM’s School of Engineering and Design is looking for a Postdoc (f/m/d) in Energy Informatics. You are
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 1 month ago
) spectral energy distribution fitting, star-forming regions/nebulae analysis, photometry, region morphology and/or catalog generation are in particular encouraged to apply. Applicants (m/f/d) should have a
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in different healthcare domains in our “AI Safety Test Bench” Coordination with our project partners the position is limited to 3 years Your Profile PhD degree in computer science or a related field
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unique three-dimensional maps of neurotransmitter receptor distributions in the human, non-human primate and rodent brain Develop efficient processing pipelines enabling the spatial integration
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to emerging carbon dioxide removal techniques. To this end, distributed pelagic imaging techniques enable the sustained observation of aquatic life and its debris, comprehensively covering the earth’s water
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and
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, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination