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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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expand and improve an existing modelling framework to predict direct and indirect nitrous oxide and methane emissions from agriculture. You contribute to the following activities: Performing a SWOT
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of dynamical systems, control of complex and uncertain systems, motion control for high-tech systems, model predictive, networked, supervisory, neuromorphic, and learning-based control, cyber-physical systems
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to contribute to a more sustainable and better world? We, Wageningen Food & Biobased Research (WFBR), are looking for a researcher data & modelling. Are you the one who will strengthen our team? What will you do
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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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to increase resource use efficiency. However, managing and optimizing these new cultivation systems requires crop models that can predict plant growth, crop yield and resource use under highly dynamic
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Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems
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greenhouses than constructing detailed CFD models for each location. Key expected innovations in this project are expected to include a hybrid data-driven and model-based predictive control approach that uses
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, these flows remain poorly understood. As a result, even the most basic properties cannot be predicted reliably. For instance, the best available models over- or underestimate the measured pressure drop in a
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Want to teach machines the mechanisms behind how the world changes — and build agents that act on them? Join us! World models are controllable, physics- and mechanism-grounded simulators of reality