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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 8 hours 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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applying Natural Language Processing (NLP) algorithms. Knowledge or prior experience in Virtual Reality technologies. Work Plan: The grant aims to develop Agricultural Simulations using Virtual Reality as a
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. Given their importance, continuous monitoring and fault diagnostics are crucial—especially as machine learning algorithms play an increasingly prominent role in predictive maintenance and reliability
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
, with application to biomedical flows (e.g. microcirculation) it is now intended to develop an improved algorithm for advanced particle tracking using machine learning. The algorithm should be tested in
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the methodologies for preventing unintended, harmful behaviors in open-source AI models. Your work will focus on the foundational challenges of safety, from mitigating algorithmic bias to ensuring systems remain
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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suitable voltage and frequency control strategies, based on state-of-the-art research, and development of dispatch algorithms for the isolated microgrid, considering the coordinated control of generation
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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