Sydney Precision Data Science Centre
Extracting insight from the data deluge
We are a world-leading precision data discovery centre that facilitates data decision making in the areas of health and wellbeing, food sciences, conservation, and biomedicine.
The Sydney Precision Data Science Centre aims to realise the University's collective research potential, make ground-breaking foundational discoveries using data-intensive science, and answer the complex challenges in biology, medicine and global health.
The purpose of the Sydney Precision Data Science Centre is to engage in high quality and transformational multidisciplinary research and to provide a research hub to all interdisciplinary researchers in data-intensive science.
We generate innovative, fit-for-purpose applied analytical methodologies that are critical to knowledge discovery through the deep integration of various quantitative disciplines and research paradigms.
This project brings together biostatistics and bioinformatics disciplines to deliver a series of tools to improve kidney disease management and access and transplantation outcomes.
The project combines expertise in bioinformatics, machine learning and statistics to integrate multi-omics data to create novel biomarkers and risk scores for coronary artery disease that is flexible, interpretable and scalable. This will close the gap between data generation and data interpretation and the gap between biomarker discovery and clinical translation.
This project brings together expertise in bioinformatics, imaging and machine learning to develop a suite of readily deployable software solutions that accelerate the processing of various biomedical data by harnessing the parallel and distributed capacity offered by modern cloud computing platforms.
This is a collection of cancer projects that requires expertise in statistics, biostatistics, imaging and machine learning to develop a suite of tools including genomics and imaging omics, that will solve major challenges in multi-morality risk prediction tools. The projects have a primary focus on melanoma and head and neck cancer.
The project embraces disruptive biotechnologies such as the recent single-cell innovation that generates thousands or even millions of cells in a single experiment and poses unique data science problems in scale and complexity. As such, it generates new computational and algorithmic challenges related to data storage, processing (including normalisation), modelling, analysis, and interpretations.
This project combines statistics, biostatistics, demographic modelling and age-period-cohort models to address data challenges associated with food quality and supplies. This includes projects that involve understanding globally competitive Australian meat value chains as well as the effects of contemporary and historical food supplies on health.
This project brings together biostatistics, precision bioinformatics and computational statistics to address pressing issues in nutritional science. This includes evaluating the effects of dietary macronutrient composition on disease outcome to facilitate healthy aging and incorporating large-scale ‘omics’ datasets to address the multi-dimensional complexity of nutritional problem.
