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(CFD), including chemical reaction models, but could also involve other modeling methods such as Density Functional Theory (DFT) or kinetic Monte Carlo. Your qualifications You have graduated at Master’s
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excite states in certain materials which can then be identified through inspection of the neutron energy spectra or emitted radiation. The project will initially involve simulation work using Monte-Carlo
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Materials 2024 (OMat24), or Open Catalyst 2022 (OC22), which will be used to refine the GenAI-proposed steps, and (iii) using the dataset generated by GenAI to parameterise kinetic Monte Carlo (KMC
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manufacture, to enable quantitative imaging. Your research will include a mix of computational and experimental work to develop and characterise these instruments. Monte Carlo simulations (using GEANT4) will
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physics or related discipline (assessed at: application/interview) Familiarity with the experimental techniques in particle physics (assessed at: application/interview) Experience in Monte Carlo modelling
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(density functional theory and ab-initio molecular dynamics simulations) with artificial intelligence techniques to parameterize machine learning force fields and kinetic Monte Carlo methods to model
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develop innovative techniques to accelerate computational methods in uncertainty quantification and data science. Potential investigation areas: • Enhancing Monte Carlo and Markov Chain Monte Carlo (MCMC
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: 4 years No. of scholarships: 5 Coordinator: Prof. Carlo Rescigno Contact e-mail: acma@ssmeridionale.it 2. Clinical and Translational Oncology (CTO) Program duration: 4 years No. of scholarships: 5
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University, Perth, WA, Australia with Dr. Navdeep K Dhami in her ARC Discovery project in collaboration with Prof. Allan Pring (University of Adelaide), Dr Carlos Rodriguez (University of Granada, Spain) and
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Simulations * Collider Physics / Jet Physics / Monte Carlo Simulations * Other machine learning applications to high energy physics and astrophysics Qualifications: * Ph.D. in Physics or related fields. (Must