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methods that will help unlock the full potential of spatial omics data Base Salary, Level A $113,634 - $125,896 p.a + 17% superannuation About the opportunity The School of Mathematics and Statistics is
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Postdoctoral Research Associate in spatial omics, artificial intelligence and computational pathology. The role will develop and apply computational methods for analysing kidney biopsy data, integrating
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for stability analysis. The project will investigate connections between the Maslov index and the Evans function, develop methods for systems with multiple timescales, and apply these techniques
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grant-funding applications. An interest in research aimed at reducing health system inequalities and improving cancer outcomes. High level statistical and data analysis skills in advanced analytic methods
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XRD, and the analysis of complex materials datasets · proficiency in quantitative analysis, computational methods and programming, with experience in AI, machine learning or data-driven materials
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Full time, fixed term position for two years. Located at our Camperdown campus. Unique opportunity to join the School of Mathematics and Statistics to work on the project "Geometric methods
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. This opportunity is ideal for an emerging researcher with strong quantitative skills, a passion for addressing climate and energy challenges, and an interest in applying interdisciplinary methods to deliver
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, probabilistic methods, or related areas. This project is part of an ambitious research program across the Schools of Civil Engineering and Project Management. The appointee will conduct original research
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capability in quantum computing, data-driven modelling, infrastructure systems, computational optimisation, simulation, probabilistic methods, or related areas. This project is part of an ambitious research
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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