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Field
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of estimators, test statistics, and predictions modelling dynamic relationships between brain activity and subjectively experienced pain at the individual level Research context The PhD is closely linked
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. The candidate will integrate quantitative 3D histology and tissue biomechanics, oculomotor behavioral tests in mutant mice, and mathematical modeling, to develop a predictive multiscale framework linking muscle
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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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. The position is particularly suitable for candidates with strong skills in applied mathematics, control, physics, or electrical engineering, and an interest in dynamic systems and modelling. Experience in system
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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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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 in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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: Pattern and Image Analysis – Lx Work Objectives: - Evaluate and compare different causality discovery algorithms under controlled and realistic conditions. - Develop a robust and interpretable causal model
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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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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