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Field
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-performance computing (HPC) environments for large-scale data analysis, including workload managers such as SLURM. For full details about this role, and other criteria, please review the Position Description
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the application of analytic techniques to longitudinal or large mental health data sets or biobanks a strong applied research orientation with a proven ability to build successful working relationships with a
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bioinformatics, programming, and large-scale data mining, within a collaborative, high-performance research environment. You’ll also contribute to service and engagement activities, helping drive innovation and
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cognitive function. Experience with meta-analysis and review-centred applications such as Covidence and Comprehensive Meta-analysis. Experience analysing data using R with big data sets. Experience in
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managing and processing large data sets and for the delivery, reporting and visualisation of data and results. Demonstrated experience in undertaking field work including planning, coordination and
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, and machine learning/artificial intelligence. This project focuses on the development of novel theoretical frameworks alongside cutting-edge computational techniques for large-scale optimisation
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of mapping in dynamic landscapes. Demonstrated skills in contemporary computing technologies and data science for managing and processing large data sets and the delivery, reporting and visualisation of data
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faculties in Australia, Macquarie University's Faculty of Arts is home to bold thinkers and passionate researchers and educators who are asking the big questions about the world. United in the spirit
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(at either level A, B, C and/or D) to support the research fieldwork, project deliverables, data governance, reporting and presentation of research findings for the ‘Measuring Digital Inclusion for First
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for Big Data Research in Health (CBDRH), strategically partnered with the School of Clinical Medicine (Women’s Health) at the University of New South Wales, Sydney (UNSW). This positioning places the NPESU