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Field
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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. While EMT simulation provides the required modelling detail, existing workflows do not scale efficiently to national and regional transmission systems.Our Vision: make EMT-based stability assessment
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project topics can be found at https://indibrain.eu/recruitment . OPEN POSITION: Project 5: Modeling Individual Brain Differences using Deep Learning & Vision Neuroscience: This project sits
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Assist in developing AI-based computational tools for analyzing biological images. Help implement machine learning, deep learning, computer vision, and image processing algorithms. Work closely with
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architectures for foundation models The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS
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and research interests, the project may focus on one or more topics such as cyber risk assessment, human–machine interaction, cyber risk communication, cybersecurity training, or organizational and
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considered. Education related to Artificial Intelligence (AI), robotics programming, computer vision, Design for Manufacturing and Assembly (DfMA), or life cycle environmental/cost assessment is considered
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). Working in the Faculty of Health and in partnership with Carl Zeiss AG and the ZEISS Innovation Hub, the successful candidate will gain interdisciplinary training spanning clinical vision science
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will operate at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
- SIPG LAB/ISR and 1801P.01460.1.04 LARSYS/ISR BASE 2025-2029 – SIPG LAB/ISR, financed by national funds through FCT/MCTES Workplan: Develop new representations for computer vision and machine learning