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actions, anticipate future behavior, and reason under uncertainty. The methodological scope includes machine learning, computer vision, multimodal perception, probabilistic modeling, and interpretable
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Range $15.61-24.99/hour Type of Position Staff Position Time Status Full-Time Required Education AA Click here for more information about equivalencies: https://hr.uky.edu/employment/working-uk
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machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal learning, and 3D perception. An affinity for translating
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uncertainty be modelled and propagated to support large-scale change analysis? Approach: You will combine advanced robotic localisation and high-resolution mapping methods with advanced machine learning feature
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uncertainty be modelled and propagated to support large-scale change analysis? Approach: You will combine advanced robotic localisation and high-resolution mapping methods with advanced machine learning feature
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Teaching the module M05 Computer Vision & Perception. Developing and delivering module content suitable for online teaching. Providing online resources and learning material for our teaching platform
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with supervisor and as a part of a team; and use or learn a range of position-related software applications. Demonstrated ability to read and interpret complex documentation required. Demonstrated strong
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, organization, and function; models of perception, cognition, learning, and behavior; and statistical and machine-learning approaches for understanding neural data and brain function. We are particularly
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
, sensor perturbations) without catastrophic forgetting, building on the team’s prior work in continual and self-supervised learning. Adaptation to simulated environments: transfer of perception modules
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, visiting researchers, master's students, etc.) Research Context Recent advances in mobile robotics have been driven by remarkable progress in perception, deep learning, and control. However, current robotic