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precipitation, leading to scaling within reservoirs and production wells that reduces operational efficiency. Predicting where these processes will occur is a challenge because they are controlled in part by
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pumping technologies for future electrified energy systems. We are currently recruiting a PhD candidate at DTU for a project on the multi-physics modelling of bearingless pumps. A parallel PhD position is
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Engineering, Control Engineering, Mechatronics, Robotics, or a related discipline with a strong focus on dynamic systems. Strong background in state-space modelling, estimation theory, and control systems. Good
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and numerical models that predict material deformation, force transmission to cells and the resulting changes in cellular mechanics and signalling. The position is primarily computational, but a
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disturbances. Current control methods generally rely on simplified interaction models based on constant aerodynamic coefficients, quasi-static approximations, potential flow models, or experimentally identified
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behaviour for system monitoring, state estimation, and performance prediction. Build computationally efficient models suitable for monitoring, performance prediction, optimization, and control, and evaluate
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STLO) (https://eng-stlo.rennes.hub.inrae.fr/ ). This work is part of the “Predicting the browning of dairy powders by kinetic modeling of Maillard reaction and caramelization during drying and storage
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University. Where to apply Website https://www.academictransfer.com/en/jobs/363990/phd-modelling-non-co2-greenhous… Requirements Specific Requirements You are/have the following personal competencies and
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, link ecological and EO data, and integrate your findings into models to predict ecosystem functioning in response to global changes and management interventions. You will learn how to publish your
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The candidate will develop and benchmark zero-shot multimodal fusion models for rare disease prediction, using melanoma as a use case. The project integrates spatial and single-cell multi-omics data with