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- INESC TEC
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- UiT The Arctic University of Norway
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the state of the art in the fields of smart buildings, digital twins, and the development of building energy optimisation algorithms; Use of methods and tools for energy systems modelling and optimization.; 3
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to grant holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The ORION project aims to develop and
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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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programme Reference Number AE2025-0594 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0594
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to support energy management in buildings, integrating optimisation and forecasting models and algorithms; - development of interactive visualisation dashboards, including front-end components and integration
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: OBJECTIVES | FUNCTIONS Develop algorithms for pre-processing of spectra, by analysing user-uploaded files to identify their origin, confirm spectra presence, and assess spectrum quality. Implement novel AI
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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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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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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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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