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Distributed, robust and adaptive model predictive control (MPC) School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline: Applications
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integration, metadata harmonization, preprocessing, and quality control of large public sequencing datasets Implement and benchmark machine-learning models for predicting biological and ecological metadata from
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24 Months, Fixed Term Whole-Time Post Position Summary INFANT Research Centre is now accepting applications for a Postdoctoral Researcher to work on the Sophie project (School-age Outcome Prediction
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. Your Role A key pillar of ECOWIND is bridging the gap between remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines
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, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling
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by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a leading role in developing and implementing predictive algorithms designed
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behavior (e.g., ignition, burning rate, fire growth). Such predictions require accurate and efficient simulation of the tightly coupled, time-dependent condensed- and gas-phase processes that control
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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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improvement. Provide validated outputs to predictive control frameworks, operator decision support systems, and sustainability assessment work packages within FLARE. Benchmark and validate AI-enabled methods
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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