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Field
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Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions in the T-PRESS Evidence Ecosystem Framework”. The primary objective of the T-PRESS consortium is to
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their application eligibility will be determined on a case-by-case basis. The start date is October 2026. Tidal stream power is a highly dense, predictable, renewable energy source. Following the successful operation
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will also collaborate with a postdoctoral researcher and another PhD candidate on creating new GPU-enabled pharmacophore searching algorithms. Prospective validation will be achieved by predicting
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, separations, and energy storage, rely on liquids operating inside nanoporous materials. At this scale, liquids behave in unexpected ways that cannot be predicted from bulk properties, yet these effects often
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mobility and vulnerability to falls. The project will combine physiological sensory biomarkers with postural control, gait analysis and real-life mobility measurements obtained using wearable sensors 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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Sustainable Healthcare Decisions. About the project The fellowship period is 3 years and devoted to carrying out a project entitled “Reliable Bayesian prediction models with uncertainty quantification
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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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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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supervising graduate students; Experience in teaching activities in higher education; Training in good clinical practice completed less than 2 years ago; Experience in quality control applied to MR and PET