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, and systematic evaluation of results. Objectives: Development and application of artificial intelligence algorithms for different use cases in the energy sector, e.g., forecasting of renewable energy
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caching algorithms for remote scenarios and reduce write amplification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Responsibilities under the grant:; - Design of a key-value storage system
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holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Study the main exact subgraph counting algorithms identified in the survey (e.g., ESU/FANMOD, Kavosh, GTrie, FaSE, ORCA
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, client devices, and the network itself; • Autonomous platform positioning and control, through the development of algorithms capable of determining suitable network configurations according to the observed
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varying viewpoints, resolutions, and acquisition conditions. ; ; ; Developing terrain- and infrastructure-based localisation algorithms that relate observations acquired by the vehicle to maps available
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in terms of localisation and navigation accuracy, but also with respect to computational efficiency, scalability, communication requirements, robustness, and real-time feasibility. Algorithms will
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of the proposed solutions. Activities will include the implementation and evaluation of algorithms for signal processing, detection, correlation, localization, and tracking of acoustic sources, as
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. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Develop optimization algorithms for predictive energy management • Model consumption, renewable generation, storage and CO₂ emissions • Test the
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. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Develop real-time optimization algorithms • Model multi-vector energy-water-hydrogen systems • Support the development of digital twins • Test the
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analysis of data from wearable and clinical monitoring devices and clinical databases. Experimental evaluation of algorithms, development, and deployment. Support in data collection and documentation