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is to move beyond traditional “check-after” approaches and instead predict and prevent errors while the radiotherapy treatment is being delivered. The candidate will build upon this existing prototype
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and observation models to reflect real-time changes in environmental conditions, enabling more accurate predictions of adaptation impacts and thereby supporting a better-informed, resilient decision
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better quality of life for patients and caregivers, and lower healthcare costs. The target is to define new intelligent computational models by reshaping risk prediction, diagnosis, and management of a
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materials to enhance the cell robustness. Work plan The work plan for the PhD thesis will be divided in three main steps: 1) A chemo-mechanical model will be built to predict the crack initiation and
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—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from
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fields). Strong quantitative skills and demonstrated expertise in predictive modeling and advanced computational methods (e.g., Multilevel Vector Autoregressive Models, Dynamic Structural Equation
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Your Job: Remote sensing data from satellites are an extremely valuable information source to improve air quality predictions. They monitor aerosol and trace gases often with global coverage, which
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to cutting-edge research projects aimed at collecting massive protein fitness measurements in service of developing a new generation of predictive models linking sequence to function. Key responsibilities will
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is searching for a Control Engineer for developing health-aware model predictive control (MPC) for fuel cell hybrid electric vehicles (FCHEVs). Fuel Cell HEVs provide a long-term solution to
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models. The candidate will be jointly supervised by Dr. Iris Groen (www.irisgroen.com ) and Prof. Cees Snoek (https://www.ceessnoek.info/ ). Want to know more about our organisation? Read more about