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Field
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Norway’s research group for User Perception and Engagement in XR Experiences. ND conducts research in networks and distributed systems of all scales, multimedia and AR/VR/XR systems, robotics and machine
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characteristics, brittleness vs. plasticity, and frictional/lubrication properties. Generate mechanistic insights linking textural dynamics to sensory perception. Integrate multi-modal datasets from different
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. Laboratory studies include collecting multimodal behavioral data, eye tracking, computational modeling, and electroencephalography data. Responsibilities Responsibilities will vary day-to-day depending on
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planning, control, and perception methods for aerial robotic manipulators (ARMs). These aerial manipulators will act as “flying hands” to support the connection and assembly of prefabricated building
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research and field explorations. Physical Grounding and Scene Understanding - Build perception pipelines that connect visual and multimodal observations to structured representations of the physical
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Huazhong Agricultural University (HZAU) | Wooldridge Number One, Eastern Cape | South Africa | 3 months ago
integrated autonomous perception-decision-execution robotic systems for farm, facility, orchard, livestock/poultry, and aquaculture scenarios, aiming for accelerated breeding, precision production, and
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and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland Norway’s research group for User Perception and Engagement in XR
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context and environmental metadata. ; Robotic inspection and mapping of deep-sea habitats, geological formations, infrastructures and environmental features. ; Deep-water perception using sonar, optical
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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Job Purpose To make a contribution to an ERC-funded project Dynamic network reconstruction of human perceptual and reward learning via multimodal data fusion, working with Prof. Marios Philiastides