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multimodal generative AI for music/audio. Check out some of our recent projects here: https://dorienherremans.com/biblio (including work on models like Mustango, SonicMaster and other generative systems
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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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Science Programs, and MS in Computer and Information Science (https://cse.aua.am/ ) invite applications for a full-time faculty position in Machine Learning at the rank of Assistant Professor, starting in
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, from linear models to deep learning, depending on what best fits a given problem. The most successful researchers will be driven by a curiosity for how their contributions fit into the larger picture of
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scoping to deployment and monitoring of production-grade models—with a focus on both Generative AI and Deep Learning. The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and brings a strong
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learning, and deep learning applied to biomedical research and medicine. • Experience in biology or biomedical research projects. • Experience with Linux, R, and Pandas. • System and server administration
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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep-learning
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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Is the Job related to staff position within a Research Infrastructure? No Offer Description You are keen on contributing to new advances in deep learning methodology for cardiac ultrasound imaging
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reinforcement learning for robotics applications. Hands-on familiarity with robotic manipulators and motion planning. Proficiency in deep learning frameworks such as PyTorch or TensorFlow. Experience with ROS