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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
Offer Description INEGI is opening a call for applications for the recruitment of a PhD Researcher in the field of Scientific Artificial Intelligence, Optimisation and Computational Modelling Applied
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holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Characterize the asset system under study, including the identification of the main critical components, the modelling
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of the research process and the results obtained. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Co-develop the requirements for optimization models, taking into account solar assets, EV chargers, and
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; • Implementation, configuration and testing of frameworks and tools in remanufacturing testbed use cases, including their integration with simulation models and Digital Twins; • Contributing to the development
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TEC. 2. OBJECTIVES: - Support the modelling of a Decision Support System aimed at defining and evaluating last-mile parcel delivery policies; - Identify, select, and apply methodologies and tools
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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