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. Through top scientific research, we push back boundaries and set a course for the future – a future that you can help to shape. The Department of Electronics and ICT Engineering Technology in the Faculty
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Department: The Center for Satellite and Earth Science Research (CSER) advances Earth system science through cutting-edge satellite technology, data-driven research, and interdisciplinary collaboration. We
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key master data domains (e.g. Person, Organisation, Vendor). The role focuses on identity resolution, survivorship modelling, API-first publishing, and event-driven data architecture — ensuring high
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for converged Wireless-opTical cOnfiguratioNs”. The research will cover three key pillars: Artificial-Intelligence (AI)-driven models in the access domain, focusing on CF technology to efficiently acquire Channel
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
remote work location, consistent with System Office policy. UNC Chapel Hill employees are generally required to reside within a reasonable commuting distance of their assigned duty station. The Data-Driven
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. Are you interested in tackling these challenges with cutting-edge AI sensing techniques? At the AISensing team we focus on AI-powered sensing technology, spanning large-scale AI models, simulation of next
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data-driven control in a collaborative and dynamic environment. About us At the department of Electrical Engineering research and education are performed in the areas of Communications, Antennas and
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] Subject Areas: mathematical modeling, statistics, machine learning, data-driven modeling, dynamical systems, optimization Appl Deadline: 2026/04/01 04:59 AM UnitedKingdomTime (posted 2026/02/19 05:00 AM
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vision foundation model capable of accelerating discovery across the life sciences. We are seeking a highly skilled AI Research Engineer to join our team and advance our AI-driven scientific initiatives
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 6 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis