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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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; Regional, national, and international collaborator programmes. For more information on our research, please see Prof. Barbour’s current group website at https://academic.sun.ac.za/barbour/Home.html , as
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: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design Creating and validating digital twin architectures that incorporate physical laws and constraints
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/security policy net assessments to address gaps in technical and non-technical SDA capabilities, and how to address permanent uncertainty in SDA analysis. Candidates with a background in space security and
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models for each study site, informed by sensor networks and image-based observations. Conduct cross-disciplinary geospatial analyses linking modeled flooding patterns with soil pathogen and participant
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of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus
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within the project) can be found at its website: https://www.mobilitydesaignlab.nl/. Job requirements The candidate should have: a PhD degree in Artificial Intelligence (AI) or closely related topics in
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continuum robotic hardware systems Integration of miniaturized actuators and sensors into continuum robotic platforms Calibration and experimental validation of the developed robotic systems, including
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grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations