241 linked-data-"https:"-"https:"-"https:"-"https:"-"https:" "Computer Vision Center" positions at Technical University of Munich in Germany
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looking for highly motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to
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, materials science, computer science, imaging science, or a related field. Strong background in neutron imaging, X-ray imaging, tomography, image processing, computer vision, or related experimental
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: [email protected] More Information https://www.cs.cit.tum.de/en/dss/home/ Print Find more topics on
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University of Munich. Previous Work https://mediatum.ub.tum.de/doc/1731060/g5zgxaj96lcyhh8gh6le1xbuu.Wetzlinger-2023-TAC.pdf https://mediatum.ub.tum.de/doc/1696192/aab7jokzk7x4paq7m2y9pa2p6.Wetzlinger
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architectures for foundation models The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS
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Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being excited to make a real impact with their
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Forschungsinstitut (https://www.dgfi.tum.de/en/). The aim of the project is to combine a low resolution, thirty year time series of sea surface height (SSH) from satellite altimetry with high resolution data from a
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country. TUM has established the Collaborative Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary
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development of ProteomicsDB with a good background in bioinformatics, data visualization, big data analytics at best in the context of mass spectrometry. ProteomicsDB (https://www.proteomicsdb.org/) is an
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Ginkgo (https://github.com/ginkgo-project/ginkgo), with the aim of improving the efficiency of scientific simulations in applications such as cardiac electrophysiology (MICROCARD: https://microcard.eu