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Field
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://www.academictransfer.com/en/jobs/363733/phd-candidate-multimodal-and-ag… Requirements Specific Requirements Profile We welcome candidates with an MSc or equivalent expertise in artificial intelligence, medicine, computer or
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mapping technologies. This PhD would particularly suit candidates with backgrounds in: Artificial intelligence or machine learning Computer science Data science or computational modelling Engineering
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Collaborate Work (CSCW), Human-Computer Interaction (HCI), Participatory Design, and Artificial Intelligence, the lab explores how AI can act as a local infrastructure for collective inquiry, knowledge building
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largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing applications. As AI models continue to increase in size and computational complexity
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Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status
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from Rolls-Royce plc. This fully funded PhD project, with support from a leading industrial partner, will explore the development of next-generation intelligent sensing and data analysis techniques
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. The focus of this PhD position is the development, characterization and experimental evaluation of advanced sensing hardware. Signal processing and Artificial Intelligence are applied as enabling technologies
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD student positions in Business Administration with a focus on entrepreneurship
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
planning and coordination of production activities in supply chains and generate managerial insights and practical guidelines for practitioners. Take part in the mandatory PhD research education program
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. There is also a need for accounting noise in Deep Learning models and quantifying uncertainty in real-world applications. This PhD studentship (scholarship) leverages large-scale Earth Observation data