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susceptible steel structures. Thus, the candidate will develop reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be
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support commercialisation of a simulated autonomous road maintenance vehicle. Study CAV interfaces and propose and design a standard API for the cloud-based platform. Key Competencies: Strong analytical and
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qualifications, academic achievements, list of publications, work history and references A copy of your academic transcript(s) Enquiries Dr Karen Little, karen.little@monash.edu , Business Manager, ITTC
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MSc in physics, applied mathematics, environmental sciences, computational science or a related field; excellent skills in scientific programming and numerical/statistical analysis of simulated and
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through soil, surface water, and groundwater systems. By validating model simulations with in-situ measurements (e.g., soil moisture, groundwater levels, surface water) and geospatial datasets (e.g
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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such as textiles. 2. Proven ability to develop and implement advanced motion-planning algorithms and real-time control schemes, ideally demonstrated through digital-twin simulations and hardware-in-the-loop
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach
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climate states. Key responsibilities To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals