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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
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workflows, including troubleshooting, iterative method development, and data-informed protocol refinement. Strong analytical skills, with demonstrated ability to manage and interpret large eDNA datasets
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workflows, including troubleshooting, iterative method development, and data-informed protocol refinement. Strong analytical skills, with demonstrated ability to manage and interpret large eDNA datasets
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immune development technical expertise in flow cytometry, single-cell analysis, microbiome analysis, and large-scale bioinformatics proven track record in nutritional geometry and global data
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 10 days ago
research labs, and develop teaching and science communication skills. The Person We are looking for a qualified computer scientist or computational linguist with demonstrated expertise in training large
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 18 days ago
psychometric equivalence across languages and contexts. Collaborate with computer science colleagues to develop novel personality instruments for unstructured text data. Position Overview This post-doc
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complex information clearly both orally and in writing. Experience in qualitative research methods and analysis, in particular interviews, focus groups and facilitating large workshops (25+ people) with
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statistical genetics to uncover the genetic and environmental aetiology of complex traits and diseases using large-scale cohorts and datasets. Our focus spans maternal health, early-life genetics, and how
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prevalence data biostatistics for clinical trials and cohort studies experience working with large, multi-wave datasets (e.g., ABS, AIHW, HILDA) reputation at a national level as influential in expanding
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of social dynamics. Motivating aims include the discovery and analysis of hidden large-scale patterns in data/models, elucidating mechanisms underlying the emergence of these large-scale phenomena and their