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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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research in digital sociology, ethnographic methods, and human-AI relationships. Your responsibilities will include: Conduct research, analysis, and publication targeting diverse audiences, including
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for the manufacture of computer chips. The project is supported by the Australian Research Council Linkage Project “Innovative Double Patterning Strategies for Integrated Circuit Manufacture” and is within
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, and inclusion , fostering an environment that mirrors our wider community. We're committed to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your
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in applying these methods to renewable energy (wind or photovoltaic) applications is highly desirable. This position will provide you with the opportunity to develop your scholarly research and
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This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong
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promoting diverse talent. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact talent@uq.edu.au . Other Information UQ is
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the accessibility of nationally significant Earth and environmental science collections, boosting the capacity and capabilities of geoscience laboratories at UWA, Analytical method development and refinement as
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regionally and soil-specific quantitative soil health scoring and benchmarking methods. Your high-level duties will include: Carry out research investigations requiring originality, creativity and innovation