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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
; - Collaborate in the writing of technical reports regarding the protocols, mechanisms, and algorithms developed; - Co-author scientific publications based on the work developed; - Prepare the research grant
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the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - collaborate in the development of new communications solutions for extreme environments; - contribute to co
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research grant Refª BI|2025/802 Project ATE – Refª C644914747-0000023 funded by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds Application
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matches the recorded motion of a group of healthy individuals and its application for the prediction of such movements to enhance human-robot collaboration. Related to this, developing and implementing
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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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process and the results obtained. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - To contribute to the specification and development of algorithms for optimizing energy systems with
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visualisation (libraries such as Three.js, OpenGL, VTK, or similar); - Advanced knowledge of optimisation algorithms; - Previous experience with software development for logistics problems; - In-depth experience
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distributed systems. Minimum requirements: - Solid knowledge of database engine implementation; - Solid knowledge of optimization algorithms (Volcano/Cascades); - Practical development experience with
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uncertainty, and explainability and reliability. The project will have an applied focus, so the aim is to develop algorithms and implement these in systems that enable testing and evaluation in collaboration
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programme Reference Number AE2025-0550 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0550