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Job Description Do you want to figure out why Bayesian deep learning doesn’t work? And afterwards fix it? At DTU Compute we are working towards building highly scalable Bayesian approximations
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: Experience with deep learning frameworks like PyTorch Experience in LLM development and/or evaluation Language requirement: Good oral and written communication skills in English English requirements
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signal-to noise Post-processing: denoising, reconstruction algorithms Comparison with high-field MRI: deep-learning and other AI modalities for low-field MRI optimization Close cooperation with
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Number: 6861527 Postdoctoral Scholar Employee - Astrophysics - Department of Astronomy Position overview Salary range: The UC postdoc salary scales set the minimum pay determined by experience level at
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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++), Deep learning tools (PyTorch) Computer Vision tools (OpenCV, MeTRAbs) English scientific communication skills. LanguagesENGLISHLevelGood Research FieldComputer science Additional Information Benefits
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
research universities in the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, robustness, calibration, bias/fairness, and/or adversarial stress-testing. - Solid programming and ML/NLP engineering skills in Python and ideally modern deep-learning stacks (e.g., PyTorch/JAX, HuggingFace