Post-Doctoral Fellow (Biostatistics and Cancer Epidemiology)

UNSW; Adelaide; Hybrid; AUD 133,000 - 156,000; Full time

Benefits offered by this job

Christmas leave

Career development

Course discount

Superannuation 17%

Retail discounts

Job summary

UNSW is offering a 2-year post-doctoral fellow position in Biostatistics and Cancer Epidemiology at the South-West Sydney Clinical School, Liverpool Hospital, with hybrid work arrangements.

The role focuses on statistical analyses of large administrative datasets to examine inequalities in cancer care, using data linkages with Census and health datasets, in a multidisciplinary team with clinicians and data scientists.

Qualifications

• PhD in Biostatistics, Epidemiology, Data Science, or related field.
• Experience with large linked administrative datasets.
• Strong skills in data analysis and causal inference.
• Experience with Stata, R or SAS, and Python.
• Emerging publication record in biostatistics, cancer and health services research.
• Ability to communicate with diverse audiences.

Responsibilities

• Perform statistical analyses of large-scale administrative datasets.
• Collaborate with clinicians and researchers across disciplines.
• Work with data linkages of Census and health data to NSW health data.
• Contribute to equity-focused cancer outcomes research.

Skills

Statistical analysis

Data management

Causal inference

Prognostic modelling

Python

R

SAS

Stata

Publication track record

Communication

Education

PhD in Biostatistics, Epidemiology, Data Science, or related field

Tools

Stata

R

SAS

Python

Job description

This Job is based in Australia

Post-Doctoral Fellow (Biostatistics and Cancer Epidemiology)

• Duration: 2-Year Fixed Term (possible extension, funding dependant)
• Employment Type: Full - time (35 hours a week)
• Duration: 2-Year Fixed Term (possible extension, funding dependant)
• Remuneration: Academic Level B $133k - $156k base (+17% super, plus leave loading)
• Work rights: Visa sponsorship is not available for this position. Candidates must hold full rights to work in Australia to be considered for this position
• Location: UNSW South-West Sydney Clinical School, Liverpool Hospital (Hybrid working)

UNSW School of Clinical Medicine

The School of Clinical Medicine encompasses all our clinical campuses and disciplines as well as several other affiliated clinical sites. We have four main metropolitan clinical campuses which include our South West Sydney Campus, St George and Sutherland Campuses, the Randwick Campus and St Vincent's Healthcare Campus. Our Rural Campuses include Port Macquarie, Coffs Harbour, Wagga Wagga, Albury and Griffith.

The Opportunity

This will be in a research-focused position working within the Collaboration for Cancer Outcomes, Research and Evaluation (CCORE), Ingham Institute, South-West Sydney Clinical School, UNSW. They will have the opportunity to refine expertise in health services and equity research and contribute to the University's standing as a national leader in the discipline.

The Post-Doctoral Fellow will have the opportunity to work on statistical analyses of large-scale administrative datasets examining inequalities in evidence-based care for cancer. The research will involve data linkages of Australian Census and other Commonwealth health and socioeconomic datasets to NSW health data. This is a unique opportunity to work within a multidisciplinary team alongside clinicians and staff specialists who provide practical, real-world insights and expert guidance to support the interpretation and analysis of complex data.

Associate Professor Mei Ling Yap

Dr Md Mijanur Rahman

Key Skills And Experience Required

• A PhD in Biostatistics, Epidemiology, Data Science, or related discipline and/or relevant work experience
• Have contributed to competitive grant-funding applications.
• An interest in research aimed at reducing health system inequalities and improving cancer outcomes.
• High level statistical and data analysis skills in advanced analytic methods including causal inference and prognostic/risk prediction modelling.
• It will be essential to have evidence of strong data management skills and experience managing large linked administrative datasets using statistical software including Stata, R or SAS, python.
• Have an emerging publication track record with high impact publication(s) within biostatistics, cancer and health services research or another related field.
• Ability to engage with a variety of audiences, tailoring communication to suit the relevant audience.

Full details can be found in the position description.

UNSW Benefits and Culture

People are at the core of everything we do. We recognise it is the contributions of our staff who make UNSW one of the best universities in Australia and the world. Our benefits include:

• 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.
• Discounts and entitlements (retail, education, fitness passport)

Applications close: 30th September 2026, before 11.30pm Sydney time.

UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.

Pre-Employment Checks: As part of our recruitment process candidates may be required to undergo pre-employment screening, which may include reference checks, qualification verification, right-to-work verification, and criminal history screening where relevant to the role. Compliance with the necessary combination of these checks is a condition of employment at UNSW. Also note that the successful incumbent will also need to undergo NSW Health pre employment checks in addition to the UNSW checks.