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triggers?). The broad project goal is to develop computational models of hearing and perception that are fitted to human perceptual measurements and that can be used to characterize and diagnose misophonia
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University Abu Dhabi invites applicants to apply for the open Post-doctoral Associate position to perform primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control
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integrated with workers and robots, as well as the subsequent generation and updating of As-Is models of the construction asset. - Development of a digital twin of the physical asset under construction
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capture and processing of point clouds through technologies integrated with workers and robots, as well as the subsequent generation and updating of As-Is models of the construction asset. - Development
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), funded by Ministerio de Ciencia, Innovación y Universidades/AEI, focused on ‘Continual Learning for Foundation Models’ where the aim is to adapt foundation models to new tasks without forgetting previous
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | about 2 months ago
attention, prediction and learning, as well as the intricate coupling between action and perception. Our research combines (1) cross-species in-vivo observations of brain electrical and neurotransmitter
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perception and mental imagery. Responsible for designing and implementing experimental protocols, including task setup, behavioral rules, and eye-tracking procedures. Duties include configuring and calibrating
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) agricultural, water company and environmental stakeholder engagement (via interviews and surveys) to review industry and public risk perceptions and attitudes, (v) the evaluation of alternative governance models
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discussion to build trust among team members by communicating ‘early and often’. Utilizes strong coping and perceptivity skills in identifying the appropriate pace of change as well as awareness of stakeholder
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this question, we combine advanced imaging techniques for recording neural activity with high-throughput behavioral training and computational modeling to study how the activity of large neuronal populations