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the Centre for Big Data Research in Health to undertake innovative research focused on improving the prevention and management of adverse events in hospitalised patients through advanced data science
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execute advanced data management and statistical analysis methods on large scale surveillance, linked and administrative datasets Draft and finalise study concept sheets, statistical analysis plans, code
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 7 days ago
18 Sep 2026 Job Information Organisation/Company AUSTRALIAN NATIONAL UNIVERSITY (ANU) Research Field Engineering Chemistry Engineering Researcher Profile Leading Researcher (R4) Application Deadline
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 5 days ago
solar cells and large-area flexible modules, with a focus on scalable deposition, device fabrication, module integration, characterisation and stability. The role will involve close collaboration with
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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. Substantial experience in large-scale national or international oral epidemiological research, oral epidemiological examinations, and the management and analysis of complex oral epidemiological data
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validate wearable data algorithms, software tools and pipelines supporting large-scale, multi-cohort research. It will contribute to the ProPASS federated data analysis platform, including testing
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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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observations/models and from models of social dynamics. Motivating aims include the discovery and analysis of hidden large-scale patterns in data/models, elucidating mechanisms underlying the emergence
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of innovative statistical methods for analysing large-scale genomic and single-cell omics datasets, identifying causal genetic variation, and improving phenotype prediction and gene prioritisation across