58 parallel-computing-numerical-methods Fellowship positions at The University of Queensland
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coherent research program and apply best-practice methodologies. Supervision and Researcher Development: Support and supervise Honours and Higher Degree by Research students, foster researcher development
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team to drive innovation in plant breeding. Key responsibilities will include: Research: Conduct and publish high-quality research, develop a coherent research program, and actively pursue competitive
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geomechanics, or ability to quickly acquire relevant domain knowledge. Proficiency in high-performance computing (HPC) for large-scale parallel simulations. Experience with advanced constitutive models and their
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advanced computational and genomic approaches. The successful candidate will work as part of a funded research project that integrates metagenomics, k-mer–based methods, and artificial intelligence
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imposed timelines/milestones. PhD (or near completion) in Engineering or Applied Science with strong expertise in CFD. Proficiency with open-source engineering software and numerical methods such as FEM
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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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to packages in the area of geospatial data science. Evidence of innovation in research with high-level skills in numerical data analysis and presentation of data. A track record of publishing in reputable, peer
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innovative methods to study digital and social media environments. Lead independent research and contribute to collaborative efforts aimed at improving the observability of digital platforms. A key focus of
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to think strategically, responding to new developments in the field by considering their impact on the current research program, moving quickly to change practices or take new directions when indicated
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research projects funded by the NCYSUR through the Australian Government, Drug and Alcohol Program. The successful candidate will contribute to high-quality research on addiction, with a strong focus on