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strongly correlated quantum systems. Experience (supported by peer-reviewed publications) with models and analytical or numerical methods/theories such as quantum mechanics, solid state physics, lattice
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and numerical models as well as constitutive model calibration and validation based on physical experimental data. Required Qualifications: A successful applicant must have a PhD in Engineering
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department. The project aims to advance predictive modeling frameworks for structural architected materials that exhibit complex instability and bifurcation phenomena. The research will involve close
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are smaller than their numerical grid-boxes (about 100 km wide) and cannot be resolved. Conventionally, clouds have been treated statistically, introducing biases. A conventional model with superior
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. The successful candidate will be fluent in both written and spoken English The primary duties for the post will include numerical modelling, risk analysis and project co-ordination. Publishing of papers in high
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and numerical algorithms for modeling and simulation of nuclear systems. Computational Nuclear Engineers within the RTHPCM group will work with group, section, and division members and external
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modelling. A background in plant ecophysiology and/or mass and heat transfer physics would be ideal but is not required. · You have numerical modelling experience. Experience with the programming
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, numerical simulators with coupled physics (flow/reactive/geo-mechanics/thermal) have been developed and often applied to predict the long-term fate of the injected carbon dioxide to ensure its secure
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including finite element simulations. You will have the opportunity to develop and test models for unique device structures including graded channel/multi-channel GaN RF HEMTs, as well as state-of-the-art GaN
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scaled models in wind tunnels. Its main advantage lies in the ability to measure wall pressure fluctuations in hard-to-access regions, such as thin profiles, the blades of a flow-straightening stator, the