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Field
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state-of-the-art facilities to work on the following: Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments. Designing
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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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. 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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techniques (especially program synthesis) to improve the explainability and robustness of AI models Participating in co-operation with Continental’s development team Interacting with Continental business areas
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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the job funded through the EU Research Framework Programme? NextGenerationEU Reference Number 2022.05284.PTDC Is the Job related to staff position within a Research Infrastructure? No Offer Description
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the laboratories of Dr. Jason Rock in the Department of Ophthalmology and Immunology and Dr. Sören Müller in the Computational Sciences Center of Excellence at Genentech. The Rock lab combines in vitro and in vivo
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
: 238003 Vacancy ID: PDS003562 Position Summary/Description: T32 Postdoctoral Fellow position. This is a one-year, time limited position with the possibility to extend to 2 years. This is a computational
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital