Centre for Big Data Research in Health

Enhancing the health and wellbeing of all, by maximising the productive use of all possible sources of health big data in medical research.

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CBDRH team working at a table

Data-driven health solutions

We are Australia’s first research centre dedicated to health research using big data. Our research is collaborative, involving codesign and coproduction methods with consumers, communities and health care providers. Together, we aim to facilitate long term translation and implementation into health policy, service and programs.

We are privileged to have many enthusiastic partners including government agencies, health organisations from the public, private and not-for-profit sectors, research funders, clinicians, health consumers and community members.

Job opportunity

Research Fellow (National Perinatal Epidemiology and Statistics Unit)

This position is expected to carry out independent and/or team-based epidemiological and statistical research using large health datasets. The Research fellow will provide support across projects within the National Perinatal Epidemiology and Statistics Unit (NPESU) in the Centre for Big Data Research in Health.

Applications close: 6th January 2025 before 11.30pm
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About us

We are Australia’s first research centre dedicated to health research using large-scale electronic data spanning the biomedical, clinical, health services and public health domains.

What is Health Data Science?
At the CBDRH, we integrate health data science into everything we do. Our science is an evolving discipline that responds to the growing number of large and complex datasets in health and medicine.
Our research
Research at the CBDRH tackles a broad range of health issues using large-scale electronic data.
National Perinatal Epidemiology and Statistics Unit (NPESU)
The NPESU is also data custodian of the Australian and New Zealand Assisted Reproduction Database (ANZARD), the Australian and New Zealand Neonatal Network (ANZNN), the International Committee for Monitoring Assisted Reproductive Technologies (ICMART) World IVF Registry, and the YourIVFSuccess website.
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Clinical Quality Registries

Clinical registries systematically collect health-related information to monitor and improve quality of care, support evidence-based research, and inform patients and healthcare professionals about specific clinical areas or treatments.

CardiacAI
The CardiacAI clinical registry supports rapid translational cardiac research and advanced AI-based decision support tool development and validation. It uses data drawn directly from Cerner electronic medical record (EMR) systems in four major hospitals in urban and regional NSW.
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HealthGym.ai
‘Health Gym’ is an open platform providing synthetic health-related data to the machine learning and clinical research communities. The primary purpose of these data is to allow researchers to easily prototype, test and compare offline reinforcement learning (RL) algorithms.
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ERICA-E-Research Institutional Cloud Architecture
ERICA is secure cloud computing infrastructure for individuals working with sensitive, often large-scale data. It provides a highly secure, yet highly functional, computing environment that enables cutting-edge data analytics and reporting.
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Machine Learning in Health Club

The Machine Learning in Health Club is a semi-formal weekly seminar hosted by the Centre for Big Data Research in Health.

Student experience

Learn more about the student experience at the UNSW Medicine & Health Centre for Big Data Research in Health (CBDRH).