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Field
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. To minimise material and energy wastage, digital models of the manufacturing processes can be developed and linked to process control and optimisation. State-of-the-art digital models and AI tools
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and
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applications. Grid-interactive efficient buildings rely on emerging digital and cyber-physical systems to optimize HVAC operations for both energy efficiency and demand response. While Model Predictive Control
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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PhD MSCA - Acoustic and Ultrasound-based Predictive Maintenance Systems for Industrial Equipment Power converters are essential in numerous applications such as industry, photovoltaic systems
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. The lack of knowledge is related to the models that should be used to auralize UAM in urban environments: new models are needed to predict noise exposure in urban cities. Traditional aircraft noise studies
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validated algorithms. The objective is to identify sensorimotor signatures of fall risk that may improve current predictive models and contribute to the development of more targeted prevention strategies
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statistical physics, applied probability, and population genetics; develop inference frameworks that link model predictions to genomic and epidemiological data; design controlled computational experiments
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failure (if they can), but they cannot explain why it happened or calculate the exact contribution of each individual stressor. Furthermore, these models often fail and make overconfident predictions when
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image data; Experience in data analysis programs, with special focus on the R programming language; Experience in the development and validation of predictive models applied to the health area