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with researchers from climate physics, hydrology, sustainability science and complex systems dynamics and apply a range of different models. Starting from the recent AMOC tipping simulations performed
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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measurements in a team of experts on and in the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. Publication of research results and
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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Lazzarini as your proposed principal supervisor, and copy the link to this scholarship web page into question two of the financial details section. About the scholarship Diabetes is the most rapidly growing
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tasks will be to: Develop and implement machine learning models for dynamic simulations of renewable power systems Develop comprehensive guidelines for verifying and testing dynamic equivalents Integrate
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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(i.e. relationally interdependent systems) and encoding nonlinearities in these. The group has plentiful in-house simulation capabilities of numerical models and access to extensive real-world monitoring
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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this astonishing picometre fabrication precision. Further aims of the project include: Theoretical modelling of nanoscale effects and processes in SNAP Development of experimental methods of picometre-precise