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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | about 2 months ago
(denoising, Mueller matrix calculation/decomposition) and AI-based diagnostic algorithms using machine/deep learning. The primary challenge will be to deliver practitioner-relevant cervical images in under 0.5
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Fluid-Structure Interaction to focus on developing computational algorithms for fluid-structure interaction problems including the multiphysics effect of electromagnetism. The Role: As a Research Fellow
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on high-speed vision perception for autonomous driving. This project aims to advance the state of the art in visual perception algorithms and real-time systems for autonomous racing, pushing the boundaries
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, AI, and other algorithmic techniques in qualitative social scientific research. In line with the interdisciplinary and reflexive ethos of DIVSOL, attention to the societal implications of AI is an
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operation. Develop modular architectures for multi-agent coordination, sensing, and communication. Integrate sensor suites, flight controllers, and swarm coordination algorithms into UAV platforms. Conduct
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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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all, of these disciplines is required. Proven track record of scientific publication. Demonstrated experience in developing/adapting computational models or algorithms to analyse biological or ecology
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opportunities exist at the intersection of mathematics, computer science, statistics, and their scientific applications, with the lines between theory, algorithm development and software implementation often
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performance. The developed methods and algorithms will be validated on both scaled in-house test setups and Å Energi’s pilot HEPs, in collaboration with Volue Industrial IoT AS. Active collaboration with other
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to the development of innovative solutions and algorithms to enhance 5G network capabilities. Work closely with the Principal Investigator (PI), Co-PI, faculty and research team to plan, track, and deliver project