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have a strong profile within computer science, computer engineering or similar, and have an interest in media deliver infrastructure, including Edge and Cloud computing We expect: A Master’s degree in
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to train tomorrows leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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methods the reliability and robustness of the hallucination detection system under diverse visual and textual conditions Primary experiments will be conducted in CARLA (https://carla.org ), enabling
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Engineering (IMSE) at The University of Texas at El Paso (UTEP) https://www.utep.edu/engineering/imse/ is a dynamic department within the College of Engineering. The department offers one undergraduate degree
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computational modelling with experimental validation. The project involves developing time- and position-dependent models of electrochemical double layers, and parameter estimation methods incorporating
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
the computational complexity of routing problems, new exact and heuristic algorithms will also be developed, based on decomposition methods and metaheuristics, ensuring high-quality approximate solutions within a
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. This PhD will design methods that enable robots to achieve more robust, accurate perception and perception-driven planning for complex processes. You will investigate solutions like multi-sensing fusion (e.g
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which of the two positions you are primarily interested in. Position 1: The E-Sailor 8 The E-Sailor 8 doctoral position focuses on developing advanced methods for E-sail tether deployment monitoring and
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mitigate hallucinations in video-based LVLMs for autonomous driving. Objectives Design, develop, and evaluate novel method(s) to detect and localize hallucinations in LVLM outputs for autonomous driving