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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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response timelines. Building on this foundation, the project will apply scenario modelling and simulation techniques to investigate emergency event propagation, routing strategies, vehicle-task assignment
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/Simulink/Python for modelling, simulation, and control design. Experience with genset systems, hybrid powertrains, or real-time control applications is highly desirable. A practical interest in system
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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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gyre (SPG) and Arctic and Antarctic sea ice cover, involving processes on smaller scales, which are often not well represented in modelling efforts focusing on the large scale tipping elements
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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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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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– 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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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