Improving Reproductive and Perinatal Health through Big Data Analytics

This project aims to address critical knowledge gaps in reproductive and perinatal health by using routinely collected linked health data and applying advanced analytical approaches. The goal is to generate actionable insights that can inform and enhance contemporary clinical and public health practices, ultimately improving patient outcomes.

Potential subareas of research include:

1. Assisted Reproduction Technology (ART)

• A: Identify factors contributing to undesirable, particularly long-term, outcomes in ART.
• B: Develop strategies to improve the outcome of ART in infertile couples.

2. Pregnancy and Childbirth

• A: Generate high-quality evidence to optimise obstetric care.
• B: Investigate the long-term outcomes of obstetric interventions to improve maternal and child health

3. Chronic diseases in pregnancy and its impact

• A: Consolidate existing evidence and identify knowledge gaps on chronic diseases in pregnancy
• B: Investigate the prevalence of chronic diseases (eg: kidney disease) and its impact on maternal and neonatal outcomes, both immediate and long term

We welcome applicants with relevant expertise in reproductive and perinatal health and/or big data analytics.

How to apply

If you have any questions and/or are interested in this PhD opportunity, please contact the Lead Investigator Wentao Li at wt.li@unsw.edu.au.