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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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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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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
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physics. You will undertake high-impact research using data from the Large Hadron Collider (LHC) Run 3, with a focus on better understanding the Standard Model and identifying potential Beyond the Standard
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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 Mathematics and Statistics, Camperdown Campus Develop statistical and computational capability for multi‑omics data analysis and drug discovery Base Salary Level A/B $ $117,936 - $157,381 p.a + 17
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to sedimentological and biogeochemical investigations contribute to modelling sedimentary copper systems and Earth surface processes analyse and interpret large-scale geospatial and geochemical datasets publish high
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 6 days ago
disadvantage on educational outcomes. This role will have a particular focus on leading statistical analysis of large population linked data. The Postdoctoral Fellow is expected to contribute towards
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heterogeneous data (free text, structured records, images, audio), including locally hosted and fine-tuned large language models computer vision for biological and medical imaging, including three-dimensional