217 machine-learning-and-image-processing-"RMIT-University" Postdoctoral positions in Germany
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- Technical University of Munich
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- Max Planck Institute for Dynamics and Self-Organization, Göttingen
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- Max Planck Institute for Plasma Physics (Garching), Garching
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- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- Max Planck Institute of Biophysics, Frankfurt am Main
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dynamism. Its status as a comprehensive university allows for multidisciplinary learning and teaching and has great potential for internationally renowned, interdisciplinary research. Almost all of its
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teach with increasing autonomy, on the way to becoming eligible for appointment to a university professorship. Your tasks: Your research lies in philosophy, educational science or experimental medicine
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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, Computer Science or related fields (for PhD); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC
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Max Planck Institute of Biophysics, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 1 month ago
(imaging) data analysis is preferred. Prior experience in microscopy is desired but not required.) Development of 3D diffusion-based single-molecule sensors (the candidate with theoretical knowledge and
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We
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chemistry to improve the safety of products and processes. At BAM we do research that matters. Our work covers a broad array of topics in the focus areas of energy, infrastructure, environment, materials, and
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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flow within cerebral aneurysms. Arterial geometries are derived from medical scans (e.g., CT) of real patients, which are suitably meshed and processed for numerical treatment using Lattice-Boltzmann