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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Study and improvement of developed algorithms - Automation of the model
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the lifecycle of AI systems, from data preparation to model use, monitoring, and updating, should be aligned with human activities, organisational processes, and decision-making in industrial contexts
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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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) Development of workflows and methods enabling AI-powered decision assistants to support full human operators control under risk and model uncertainty, and considering human-AI co-learning.; 2) Develop
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of generating, from SQL queries, eBPF code executable in the kernel.; 2. Query planner optimization: definition of a cost model that estimates the execution cost of each operation in kernel space
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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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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning
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of essential components for creating a decentralized data space that allows data sharing in an interoperable way, both at the model level and at the data transfer protocol level. Empirical studies will be used
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coupling systems.; • Develop technical skills in electromagnetic modeling and simulation tools, as well as in energy efficiency optimization algorithms.; • Consolidate the ability to write scientifically and
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applications.; - Advanced knowledge of 3D modeling (3D modeling, UV mapping, texturing, polygon optimization). Minimum requirements: - Experience with the Unity game engine; - Experience in creating 3D models