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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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. Work will emphasize the development and analysis of advanced methods in areas such as sparse signal recovery, compressed sensing, and statistical estimation, with a particular focus on their role in
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and automata, and the interaction between formal methods and artificial intelligence. We welcome candidates interested in topics ranging from foundational theory to the development and evaluation
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, memory usage, and scalability (as a function of network size and the size k of the subgraphs); - Research the most recent developments (post-2019/2021) in the field to identify any new algorithms
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applications. ● Research and development of real-time estimation algorithms and adaptation to operating conditions Where to apply Website https://www.unimore.it/it Requirements Additional Information Eligibility
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control algorithms and optimization frameworks for adaptive neuromodulation strategies aimed at stabilizing sleep and mitigating seizure burden. Pipeline Development & Data Curation: Build, automate, and
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). Design and fabrication of the calibration test phantoms Developing and testing acquisition software, and implementing image analysis algorithms and localization methods. Where to apply E-mail
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systems, autonomous vehicle control, robotics, numerical simulation and the ability to develop algorithms in research environments will be an advantage. - PROFESSIONAL EXPERIENCE. 50 % Prior experience
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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of advanced Federated Learning algorithms. The research activity will be aimed at the study, implementation, and validation of distributed learning solutions. Where to apply Website https://pica.cineca.it/unina