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requirements, as well as the design of data models, synchronisation algorithms and analysis and learning models applied to brain and physiological signals. The objectives of this fellowship are: 1. To survey
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algorithms. Analyzing results and contributing to scientific publications in peer-reviewed journals (expected 3 papers), presenting at meetings and international conferences. Taking part in the teaching as
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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algorithms. Analyzing results and contributing to scientific publications in peer-reviewed journals (expected 3 papers), presenting at meetings and international conferences. Taking part in the teaching as
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: neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 1 month ago
-objective optimization and control algorithms to orchestrate EV charging and discharging in large buildings within a transactive energy framework, coordinating them with stationary storage and other demand
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, and data analysis for human subjects research. · Develop and apply computational models and algorithms to support robotic augmentation studies. · Contribute to manuscript preparation and dissemination
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only within dense, highly interacting systems, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of