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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
-scale neuroimaging datasets. Responsibilities for this position includes: * Developing deep-learning approaches for insight and analysis about mouse behavior from video * Machine Learning: use your
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Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and
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the medium and long term. We are looking for a Machine Learning Research Engineer: The ideal candidate will bring deep expertise in state-of-the-art deep learning methods applied to computer vision, 3D
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Learning, particularly Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models, including hands-on implementation Strong understanding of machine learning models
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position within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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, neuroscience, or a related field (industry postdoc counts) Additional Preferences: Proficiency in Python and deep experience with ML/Deep Learning frameworks (e.g., PyTorch, Tensorflow, JAX, HuggingFace). Hands
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technologies-including gradients, RF coils, field cameras, image reconstruction strategies, and AI/Deep Learning approaches-and to integrate these advancements into the Center's research infrastructure. Key
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future of our employees. From robust health benefits to generous retirement contributions and an array of family-friendly programs, Duke invests in every member of our community. Learn more at: https
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activities, I have gathered experience with machine/deep learning, and can demonstrate a strong affinity with these fields. Prior experience with computer vision is a plus. I am proficient in Python and am
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or equivalent) Strong programming proficiency in Python Experience with deep learning frameworks such as PyTorch and/or TensorFlow Experience using data science libraries (e.g. NumPy, Pandas, SciPy, scikit-learn