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Simulation” (Reference: PID2024-157499OB-C31). This project focuses on the development of advanced computational models and optimization techniques for improving the performance of cochlear implants. It
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in conjunction with the industry partner, this PhD project aims to develop a reliable numerical modelling framework capable of: (i) simulating coupled heat and fluid flow within deep geothermal
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aims to develop computational models to support the optimisation of plasma atomic layer deposition equipment. The PhD student will undertake numerical simulation, optimisation studies, and explore
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of this proposal is to investigate properties (and discover novel exotic phases) of the models with many competing energy scales originating from spin, charge, and orbital degrees of freedom, i.e., to investigate
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validation and mechanistic interpretation of large simulation datasets. The project is led by Dr. Pau Ferri Vicedo within the group of Dr. Mercedes Boronat, and benefits from a unique environment at ITQ, where
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of Public Health and Primary Care. The post-holder will contribute to the development and application of a simulation model exploring optimal approaches for iron supplementation in blood donors in England
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-informed / simulation-aware modeling Efficient algorithms for design-space exploration (e.g., surrogate modeling, Bayesian optimization, differentiable programming) Hybrid approaches combining data-driven
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machine-learning algorithms, and with lightning-fast Maxwell solvers for scattering simulations. You will not only work on the 3-D models in theory; you will also be trained in operating advanced microscopy
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Energy Modelling”. The PhD candidate will be supervised by supervisors from DTU and Chalmers. This project will integrate energy technology, building physics, HVAC systems, control systems architecture
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learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with, enhance