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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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deep learning approaches, with a particular interest in developing methods capable of handling scarce or corrupted data, designing methods for specific imaging modalities, or understanding and
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international collaborators to extend the Institute’s impact, profile and reputation coordinate and contribute to high-quality teaching and learning, including the successful supervision of higher degree research
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Urbana-Champaign, seeks faculty who are interested in future, part-time Lecturer and Instructor positions to help teach existing courses throughout the year. This is not a full-time position, but rather
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on lncRNA structure. These experimental constraints will then be used to guide deep learning-assisted RNA 3D structure prediction tools, in order to generate ensembles of structural models. Clustering and
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: Proficiency in Python and deep experience with ML/Deep Learning frameworks (e.g., PyTorch, Tensorflow, JAX, HuggingFace). Experience with RL and post-training methods (PPO, GRPO, DPO, reward modeling, RLHF
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excellence as inextricably linked. Our faculty combine high-impact scholarship and outstanding teaching with a deep commitment to inclusive excellence and we expect successful candidates to show a record of
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
additional days per year, including your birthday Minimum Requirements: PhD in Engineering Experience in Machine Learning, Deep Learning, reduced-order modeling, or physics-informed models Knowledge
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine