Post-Doctoral Fellow (Biostatistics and Cancer Epidemiology)

About the role

Full-time (35 hours per week), 2‑year fixed term (possible extension, funding dependent) Post‑Doctoral Fellow in Biostatistics and Cancer Epidemiology based at UNSW South‑West Sydney Clinical School, Liverpool Hospital (hybrid working). The role sits within the Collaboration for Cancer Outcomes, Research and Evaluation (CCORE), Ingham Institute. You will refine expertise in health services and equity research, conduct statistical analyses of large‑scale administrative datasets to examine inequalities in evidence‑based cancer care, and link Australian Census and Commonwealth health/socio‑economic datasets to NSW health data, working alongside clinicians and specialists in a multidisciplinary team.

Responsibilities

• Perform statistical analyses of large‑scale administrative datasets to examine inequalities in evidence‑based cancer care.
• Link Australian Census and other Commonwealth health and socioeconomic datasets to NSW health data.
• Work within a multidisciplinary team alongside clinicians and staff specialists to interpret and analyse complex data.
• Contribute to health services and equity research aimed at reducing health system inequalities and improving cancer outcomes.

Requirements

• PhD in Biostatistics, Epidemiology, Data Science, or a related discipline (or equivalent relevant work experience).
• Experience contributing to competitive grant‑funding applications.
• Demonstrated interest in research that reduces health system inequalities and improves cancer outcomes.
• High‑level statistical and data analysis skills, including causal inference and prognostic/risk prediction modelling.
• Strong data management skills and experience managing large linked administrative datasets using Stata, R, SAS, or Python.
• Emerging publication track record with high‑impact publications in biostatistics, cancer, health services research or a related field.
• Ability to engage with diverse audiences and tailor communication appropriately.

Skills

• Advanced analytic methods: causal inference, prognostic/risk prediction modelling.
• Statistical software: Stata, R, SAS, Python.
• Data management of large linked administrative datasets.
• Statistical analysis and interpretation of complex health data.
• Effective communication tailored to varied audiences.

Benefits

• Additional 3 days leave during Christmas holidays.
• Career development opportunities.
• Up to 50% discount on UNSW courses.
• Flexible 17% superannuation contributions, additional leave‑loading payments and salary sacrifice options.
• Discounts and entitlements (retail, education, fitness passport).

Pay

Academic Level B salary range: $133,000 – $156,000 base, plus 17% superannuation and leave loading.

Schedule

Full‑time, 35 hours per week.