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on computer vision. The role involves developing and advancing novel algorithms for emerging challenges in computer vision, including continual learning and few-shot learning. The candidate is also expected
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, Computer Engineering, or a related field. Strong background in smart contract security, blockchain systems, or software security. Experience in program analysis, formal methods, or vulnerability detection
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evaluation of the project’s core technical components in expert-in-the-loop agentic AI for manufacturing. Develop process-centric AI methods and software tools for BPMN modelling, Petri/CPN formalisation
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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simulation and real-world robotic systems. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a
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Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written communication skills In-depth knowledge
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recruiting a research engineers or fellows, as part of a wider project, to conduct research on: Signal processing combined with AI-based modification on speech signals. The need is for a real-time system, so
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technical support and feedback. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player
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engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written communication skills In-depth knowledge
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for the development of Performing literature review and background study on multi-modal AI safety Apply knowledge on large multi-modal models to optimize training and inference processes Conduct experiments to compare