182 postdoc-in-thermal-network-of-the-physical-building Postdoctoral research jobs in Germany
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=finley&sub_page=research The SNQS group performs research funded by diverse sources including the German Science Foundation (DFG), the Federal Ministry for Research, Technology and Space (BMFTR
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
Prof. Dr. Eberhard Bodenschatz, who directs the Laboratory for Fluid Physics, Pattern Formation and Biocomplexity (LFPB). We are an international research institute conducting both experimental and
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enthusiastic interdisciplinary team in an outstandingly equipped newly build scientific environment. Sound command of the basic wet lab technologies in biochemistry (DNA, RNA and protein) and previous experience
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19.05.2025 Application deadline: 31.07.2025 The group “Physics of molecular and biological materials” at the University of Tübingen is searching for Post-doctoral researcher in Physics (m/f/d, E13
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to graduate before the appointment date) in Solidstate Physics, Chemistry, Materials Science, or related fields. Prior experience with thermoelectric materials and modules is a valuable asset. We seek
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of pragmatic reasoning about Common Ground, incorporating insights from probabilistic pragmatics (in particular, Rational Speech Act models), cognitive psychology (in particular, dual-process models
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through taking on a central role in one of the Center’s ‘Research Platforms’. Equally qualified applicants with disabilities will be given preference in the hiring process. The University of Tübingen is
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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imaging technologies for the investigation of biomedical questions. RESPONSIBILITIES: You will generate fusion construct of plexins receptors with fluorescent proteins or tags for advanced microscopy You
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning