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simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power consumption and
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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or international conference. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Research and development of algorithms for analyzing signals acquired in real time by a system with integrated
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insurance, supported by INESC TEC. 2. OBJECTIVES: Study the state-of-the-art in space robotics, focusing on navigation, control, and gas propulsion systems.; • Develop navigation, detection, and localization
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17172 (COMPETE2030-FEDER-00864900) co-funded by the ERDF - European Regional Development Fund through Innovation and Digital Transition Program - COMPETE 2030 under the scope of Portugal 2030 and by
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, ensuring the quality and consistency of the datasets used.; 2) Development and implementation of computer vision algorithms for detecting and analyzing RBD-specific behaviors in vPSG videos. 3) Integration
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Applications are open for 1 Research Scholarship, within the framework of the project Direção Serviços Administrativos Polo Oeiras Workplan: Development and analysis of the Oeiras Campus of the IST as an
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regarding the developed food product; Develop technical sheets and evaluation questionnaires adapted to the target audience; Support the facilitation of workshops in collaboration with senior researchers
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. or - Holder of an academic degree enrolled in a non-academic degree course integrated in the educational project of a higher education institution, developed in association or cooperation with one or more R&D
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 6 days ago
). Develop an accompanying uncertainty‑quantification (UQ) layer on top of EM to produce calibrated credible/prediction intervals. Train, validate, and stress‑test on ECoG data, benchmarking against