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classified as a Research Officer (RO), a group that is unique to the NRC. Candidates are remunerated based on their expertise, outcomes and impacts of their previous work experience relative
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Aalborg University’s problem-based learning (PBL) model. The position is anchored in the HumanMachineInteraction research environment at Department of Architecture, Design and Media Technology at Aalborg
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. Caterina De Bacco from the Network Architecture and Services Group. You’ll become part of a diverse, enthusiastic team of academic staff, PhD students, and postdocs in the Network Architectures and Services
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Lawrence Berkeley National Laboratory is hiring a Quantum Computing Technology Researcher to join the Advanced Technologies Group (ATG) within the NERSC division. You will apply expertise
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 17 days ago
3 Apr 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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. The robotics group at NMBU conducts research in two key areas: (1) mobile robotics for agriculture, and (2) manufacturing and food processing. This PhD position falls within the first area, targeting the design
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, the Optimized AI team focuses on computing techniques to scale up a wide range of AI approaches and drive the SW-HW-Technology co-optimization. We analyze and implement AI models and software architectures while
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will be part of the ELCA (Electronic Circuits and Architectures) group in the Microelectronics Department. The ELCA group conducts world-leading research in RF and mixed-signal integrated circuits
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technologies and AI for developing community-led conservation strategies of heritage buildings at risk. This exciting opportunity is based within the Architecture, Culture and Tectonics Research Group
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environment. Key research Objectives: AI Innovation (Taxonomic Identification): Developing and optimizing deep-learning architectures (e.g., YOLO) for the automated detection and classification of nocturnal