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Field
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sensing systems Design and validate machine learning models for predictive monitoring of physiological states Analyse large experimental datasets and quantify sensor performance (accuracy, robustness
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fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind
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assessments: both predictions and reference data change over time, requiring methods that account for temporal misalignment. Variable observation density: seasonal cloud cover, satellite revisit times, and
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crystallization from mixed salt solutions and elucidate salt weathering mechanisms at micro and macro scales in heritage materials. Your work will bridge the gap between theoretical predictions and real-world
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plus. Previous experience and strong interest in control and data-driven modelling. For instance, a previous experience with model predictive control, reinforcement learning, or automatic demand response
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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Towards a Flower Waste Biorefinery: Predictive Enzyme Design for Bio-Based Chemicals This exciting opportunity is based within the Faculty of Engineering, which conducts cutting-edge research in
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, the project will establish predictive frameworks capable of optimising process parameters, controlling microstructure evolution, and improving part quality in real time. Robotic platforms will be used
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recrystallization and control nucleation for biomedical applications in e.g. heart and kidney cryopreservation. Where to apply Website https://www.academictransfer.com/en/jobs/359905/phd-in-de-novo-design-of-ice-bi
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- and risk optimal installation and operation of offshore wind farms depend on accurate forecasts and predictions of environmental conditions and response of vessel and auxiliary systems. The focus