56 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Technical University of Munich
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The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
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Technology (CIT) and TUM School of Medicine and Health is offering a 2y-4y postdoctoral full-time position in medical machine learning. The Computational Pathology Lab (https://schuefflerlab.org
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at the workplace, from compute and GPU servers to supercomputers Opportunity for a PhD (Dr. rer. nat.) in one of the group’s diverse research areas Salary according to the public service pay scale (TV-L E13
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://mediatum.ub.tum.de/doc/1696192/aab7jokzk7x4paq7m2y9pa2p6.Wetzlinger-2022-NAHS.pdf Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related
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04.04.2025, Wissenschaftliches Personal The Chair for Computer Architecture and Parallel Systems (CAPS) offers this position as part of the DARE-project funded by the EuroHPC JU bringing together
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. Requirements: Completed university degree in computer science or applied mathematics, remote sensing, geophysics, physics, or related areas Expertise in computer vision and/or machine learning (deep learning
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
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of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq