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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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O’Shea (Woods Institute) Stanford Departments and Centers: Woods Institute Postdoc Appointment Term: Initial appointment is one year, with a second year contingent on funding, results, and mutual agreement
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 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 | about 5 hours 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
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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
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artificial intelligence—especially deep learning—offers transformative potential for developing next-generation earth system models. Recent breakthroughs, such as neural network-based short-to-medium term
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Research, or a related field. Solid research background and practical experience in one or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application
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, deep learning and AI technologies while anticipating faculty needs and strategically advocating for growth in Princeton-offered services. Responsible for understanding changes to campus need and
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. Panagiotis Papadakis and Associate Prof. Mihai Andries Keywords: Deep learning, event cameras, human skeleton, pose estimation, action recognition Where to apply Website https://imtatlantique.fillout.com
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decision-making in multi-agent autonomous systems by leveraging and combining deep-learning based motion predictions and optimization-based motion planning. Key research questions include multi-modal