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                We are looking for a Research Fellow to conduct the research for the project entitled “Manual Assembly Job Quality Inspection”. The role will focus on research and development of AI algorithms 
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                —specifically fine particulate matter, heat, and humidity—in Philadelphia neighborhoods. The fellow will extend existing research in AI- and data-driven modeling of building systems by developing algorithms and 
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                vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and 
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                research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins 
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                . Develop intelligent algorithms that allow cooling systems to be controlled based on sensor inputs, ensuring adaptation to different scenarios and operating conditions; 4. Integrate and validate 
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                Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 days agomanagement from water and energy sensors; Development of algorithms to improve data collection pipelines from water and energy sensors; Analysis of water and energy datasets using AI techniques, including 
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                settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help guide and mentor graduate students and other junior team members working on the project 
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                degree in informatics. Work plan: 1- Review of the literature on cooperative air transport and multi-agent control; select drone platforms and tools. 2- Evaluate and simulate sensor configurations for pose 
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                . Responsibilities* Design, implement, and evaluate LiDAR-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help 
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                aims to define the optimal specifications for spaceborne hyperspectral sensors to detect diseases in Australia’s key wheat and barley crops. The successful candidate will lead the development and