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Field
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nitrogen-containing products and assess system performance. You will contribute to the design and testing of the prototype system, analyse experimental and simulation data, and publish the resulting research
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of single vortex in superconducting nanostructures including the design and fabrication of samples using electron-beam nanolithography and performing the corresponding simulations using the Ginzburg–Landau
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development of open-source, machine learning–based software for inferring evolutionary history from genomic data. Design and run population genetic simulations to generate training data and validate theoretical
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. You will build simulation agents that predict materials properties (such as Li-ion conductivity in solid electrolytes) autonomously and at scale, validate them against thousands of real A-Lab
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problems in bioinformatics. This project is part of the Faculty of Science's new Quantum Simulation for Molecular and Material Design (Q-MMD) programme. You will join a growing interdisciplinary team at
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ice, using a framework consisting of an ocean Large Eddy Simulation (LES) and a Discrete Element Model (DEM) of sea ice. Results from these simulations will be validated against a combination of in-situ
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from human cochlear implant users with computational modeling and simulation. Research approaches will include electrophysiological recordings of auditory nerve responses, computational modeling and
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developing and running hydrologic and land model simulations and a working knowledge of high-performance computing environments. Specific responsibilities will involve the use of ATS-EcoSIM, a new version of
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-particle physics, predictive modeling, and AI-enabled digital twins for magnetically confined fusion plasmas in tokamaks. The research will combine high-fidelity simulations, reduced transport modeling
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close to completion) in a relevant area of astrophysics or physics, and should have experience in Type Ia supernova cosmology (supernova modelling, simulations, data analysis and statistical methods) and/or