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Join an ARC-funded research project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims to improve fluid-dynamical
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project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims to improve fluid-dynamical understanding of how magmatic ore
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, apply appropriate analytical or numerical methods, interpret results, and contribute to the preparation of publications and research presentations. Demonstrated ability to work independently while
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formulate and investigate complex research problems, apply appropriate analytical or numerical methods, interpret results, and contribute to the preparation of publications and research presentations
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particular focus on flexible molecular crystals. Undertake molecular synthesis, crystal growth and advanced characterisation, develop and implement diffraction methods, including at major facilities, and
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imaging datasets. Strong technical knowledge across the data lifecycle, including research data architecture, data pipelines, database management, SQL, REDCap, cloud or high-performance computing
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rural communities. Working alongside leading researchers in a supportive, inclusive and innovative environment, you will play a key role in advancing high-quality mixed-methods research, fostering
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external funding, apply rigorous quantitative and qualitative methods, and translate evidence to inform policy and practice. Teaching: Develop and deliver undergraduate and postgraduate teaching across
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: Research: Lead or contribute to the development of innovative statistical methods for analysing large-scale genomic and single-cell omics datasets, identifying causal genetic variation, and improving
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research, implementation science, co-design, and person- and family-centred care, including experience in qualitative, quantitative, and/or mixed-methods research. Experience conducting research across