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Field
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challenge is therefore to develop efficient surrogate models capable of rapidly predicting macroscopic mechanical properties directly from microstructural descriptors while preserving the underlying physical
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is to design a data architecture capable of harmonising sensor data and integrating them with artificial intelligence algorithms for predictive irrigation management. The research will include
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these areas under warming climate after the ice ages? These are central questions for both Biogeography and Quaternary Palaeoecology, and the answers provide the basis for predictions of ecosystem and species
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sound statistical models and methodology for the data-driven analysis of complex and dynamic systems, with the goal of enabling predictive, prescriptive, and pre‑emptive analytics. We work closely with
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data to inform and validate modelling work within a NERC-funded interdisciplinary project. The NERC-funded project develops a new development-centric framework for understanding adaptation under
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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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comparing our experimental observations to predictions made using the Standard Model of Particle Physics. I am a member of the LHCb collaboration, one of the four large experiments at the Large Hadron
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
predictions for digital‑twin applications. Your responsibilities include: Development and implementation of thermo‑mechanical models in FEniCSx Integration of FEM models into neural operators and PINNs
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for new wind farms. In this context, accurately predicting the propagation of wind turbine noise in the atmosphere is essential to better understand the underlying physical mechanisms and to conduct
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challenge is therefore to develop efficient surrogate models capable of rapidly predicting macroscopic mechanical properties directly from microstructural descriptors while preserving the underlying physical