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modelling approaches, including integrated assessment modelling, material-flow analysis and life-cycle assessment, while developing robust and reproducible workflows using large and complex datasets
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arising from finite fields, projective and polar spaces, and related structures. Apply computational methods (e.g. Magma, GAP, SageMath, Python) to test conjectures and explore new mathematical directions
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reduction for data with complex structures, including but not limited to, multi-way clustered, spatial-temporal, and network dependence. The successful applicant will be jointly supervised by CIs Linh Nghiem
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of statistical dimension reduction for data with complex structures, including but not limited to, multi-way clustered, spatial-temporal, and network dependence. The successful applicant will be jointly supervised
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algebraic constructions of graphs arising from finite fields, projective and polar spaces, and related structures. Apply computational methods (e.g. Magma, GAP, SageMath, Python) to test conjectures and