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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 6 days ago
). Label-driven / weakly-supervised CNNs for multimodal deformable registration (arXiv / MICCAI threads) — key papers showing deep learning approaches for fast, deformable registration. https://doi.org
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partners, participate in scientific project meetings, and present your work at leading conferences and workshops in glaciology, ice-ocean interactions, and deep learning. Where to apply Website https://work4
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about where a new hire would be placed on the range. To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation
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graduate degree or an advanced level (higher education) in the research subject or equivalent competence. Experience with deep learning and machine learning tooling.· In-depth knowledge of deep generative
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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: Experience in deep learning, machine learning and medical imaging processing Programming experience: Python, MATLAB, SPSS, Shell. Experience in working with Linux workstation. Excellent verbal and written
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Expertise: Familiarity with supervised/unsupervised learning (regression, classification, clustering), ensemble methods, and deep learning architectures (CNNs, RNNs). Experience with explainable AI (e.g
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for students with disabilities and providing disability support and resources. The vision of DRS is to envision a learning community that values people with diverse abilities and demonstrates through its actions
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multi-omics data and the use of machine learning and data science techniques. Strong publications record according to his/her career stage. Skills: Excellent programming and scripting skills, with deep
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adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer vision; machine intelligence