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increasing relevance today due to its ability to bridge the physical, digital, and social domains. CPSS are integral to the modern world, shaping the development of intelligent systems that respond dynamically
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17 Jan 2026 Job Information Organisation/Company CNRS Department Centre de recherche sur l'hétéroepitaxie et ses applications Research Field Engineering Physics Technology Researcher Profile First
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About The University of Texas at El Paso: The University of Texas at El Paso (UTEP) is a Carnegie R1, opportunity, and community engaged university at the heart of the U.S.-Mexico border region
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Project Overview This is an opportunity to conduct fully funded research under the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex. The impact of
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established world class research groups. 85% of our research is classed as "world-leading" (4*) or "internationally excellent" (3*) and our research collaborations and networks extend nationally and
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Project Overview This is an opportunity for a person from an underrepresented group to undertake a fully funded master’s degree followed by a fully funded interdisciplinary PhD research degree under
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PhD Student position in LiFi Systems for Unmanned Aerial Vehicles - Pervasive Wireless Systems Group
Wireless Systems Group. Where to apply Website https://networks.imdea.org/job/phd-student-position-in-lifi-systems-for-unmanne… Requirements Research FieldEngineering » Electrical engineeringEducation
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. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to support the development of sustainable, resilient, and
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
Job Code: Tü_107 Job Offer from March 06, 2026 The Max Planck Institute for Intelligent Systems (MPI-IS) conducts research to advance intelligent systems that perceive, learn, and interact. Through
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The Max Planck ETH Center for Learning Systems (CLS) addresses cross-disciplinary research questions in the design and analysis of natural and man-made learning systems. The excellent engineering