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Field
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networks by analyzing their dynamical systems and probabilistic asymptotic behavior, improving and generalizing diffusion-based generative AI using insights from numerical and stochastic analysis, and making
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the DROPapp by integrating local and scientific knowledge. In this project, you will integrate the local forecasts based on observed local ecological indicators and scientific forecasts based on numerical
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predictions to conventional continuum predictions to understand the relationships between the different theoretical frameworks. The analysis will be accompanied by detailed numerical computations in
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-energy impact events using LS-DYNA and other applicable numerical analysis methods/computer simulation codes. Prepare and submit proposals/budgets to acquire new funding. Meet with prospective clients
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candidate will have a unique opportunity to work closely with researchers and technical experts from CSIRO in a multi-disciplinary team environment. The project will provide numerous research and development
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on numerical aspects of the network model analysis. Being part of the wider Mathematical Neuroscience research theme within the School of Mathematical Sciences which currently includes 7 members of academic
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partnership with the Odysseus Space company as part of the Simulator development for the optical slant path program. This PhD project aims to develop an analysis tool for the optical ground-to-satellite links
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workflows for descriptor based microstructure reconstruction to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property
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: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
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magnetic components of the dynamo are to be simulated numerically. Your profile: Potential candidates (m/w/div) should hold a Masters or Diploma degree in Materials Science, Mechanical Engineering