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ARIA project Enforcing Safety in Cyber-Physical Systems via Proof Certificates, and focus on the design, development, and application of Safe RL algorithms as well as their verification via Proof
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the development of AI-powered smart care solutions. The position is at the Department of Computer Science, Electrical and Space Engineering, Division of Computer Science, at Luleå University of Technology (LTU
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(AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care
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sensor fusion frameworks using cameras, LiDAR, depth sensors, and other sensing technologies. Develop object detection, segmentation, tracking, and pose estimation algorithms. Develop navigation
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sensors, and other sensing technologies. Develop object detection, segmentation, tracking, and pose estimation algorithms. Develop navigation, localisation, path planning, and collision avoidance algorithms
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
professional opportunities that span the campus and community. University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning
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research on shipping and port operational optimization, maritime decarbonization, data analytics, and the development and application of novel methodologies (including LLM-based prediction and optimization
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or signal analysis, data engineering, and healthcare data governance. Adept at developing/validating AI algorithms, and adhering to regulatory and privacy standards. Desirable: PhD in Computer Science, AI
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop