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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 1 month ago
-FEDER-00818200 and the acronym flexREC, financed by FCT, the European Regional Development Fund and national funds through the program MPr-2023-12l, in the following conditions: Scientific area
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Applications are open for 1 Research Studentship, within the Recovery and Resilience Plan (RRP) project “Alliance for the Energy Transition” Workplan: This research fellowship will focus on the development
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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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, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis
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that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field
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, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis
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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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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