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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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Solution to Improve Care and Optimize Resources for Frequent Emergency Users”, (ref.ª 2024.07543.IACDC, financed by "RE-C05-i08.m04 – "Support the launch of a program of R&D projects aimed at the development
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clinical data and machine learning algorithms. The main activities include: Support for AI Model Development: • Collaborating on the training of predictive models under the supervision of the scientific team
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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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position to a Research Grant within the framework of the Shift2SDV – “a common Software development framework and hardware independent microservice-oriented middleware architecture for the stepwise migration
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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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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