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with symptoms. However, our brain operates differently between sleeping and waking brain states, and an optimal system should take this into account. The aim of this project is to develop brain state
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data preprocessing, algorithm development, and optimization techniques. Excellent communication skills in English. Prior experience with environmental or photocatalytic systems is a plus. A fully funded
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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-terminal antennas and beamforming operating in FR1 bands and future FR-2, enabling robust terrestrial–satellite integration for safety-critical air mobility services. To develop AI-based algorithms
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 14 days ago
to be carried out focus on the daily operational activities of home hospitalization units, with the goal of developing optimization models and algorithms to support the planning of routes, schedules, and
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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PhD Scholarship – Development of novel Radiotracers for the Fibrosis Detection - PhD scholarship available with an International Team Job No.: 648919 Location: The Alfred Centre Employment Type
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tagging algorithm development as well as physics data analysis, with a focus on Higgs boson physics, top quark physics, and searches for new physics signatures. This is what you will do After the discovery
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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with Rolls-Royce (Enhanced Stipend) Development of Advanced Barrier Coatings for extreme environments Background Applicants are invited
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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis