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Research associate - biostatistics

Sydney
Euraxess
Posted: 11 May
Offer description

University of Sydney – Researcher Profile – Recognised Researcher (R2) / Established Researcher (R3). Application Deadline: 7 Jun 2026. Type of Contract: Other. Job Status: Full time. Not funded by EU programme. No research infrastructure related position.

Offer Description

* Full time, fixed term opportunity for 12 months with possibility of extension
* Exciting opportunity to be a Biostatistician based at the Charles Perkins Centre
* Base Salary starting at $89,831 - $121,054 + 17% superannuation

About the opportunity

We are seeking a Biostatistician to apply and further develop expertise in research methodologies and statistical analysis within population-level epidemiological research. The role spans lifestyle epidemiology, multi-omics, and cardiometabolic health, with a focus on generating high-quality, data-driven evidence. The successful candidate will contribute to research projects both independently and collaboratively, supporting study design, advanced analyses, and the translation of findings.

Your key responsibilities will be to:

* contribute to the design and analysis of epidemiological and clinical studies, including longitudinal and time-to-event data
* apply advanced statistical modelling techniques using R, demonstrating strong proficiency in data analysis and reproducible workflows
* manage large health research datasets and data access applications
* provide statistical advice and mentoring to students within the discipline and external colleagues and collaborators
* contribute to drafting of scientific papers
* develop and refine independent research skills under supervision of senior academic staff
* carry out administrative tasks efficiently, demonstrating strong organisational and time management skills
* contribute to a positive workplace culture that values diversity of thought, collaboration, excellence and outcomes
* undertake other duties and contribute to projects appropriate within the classification level as required

About you

Qualifications and experience:

* Masters/PhD in a relevant field is preferred or an equivalent combination of relevant training and experience
* demonstrated understanding of statistical modelling approaches commonly used in epidemiology (e.g., regression, survival analysis), with willingness to develop further expertise
* experience conducting original research and engaging in scholarly activity
* ability to work with complex, large-scale cohort or clinical datasets is desirable
* Demonstrated initiative and ability to deliver high-quality work in both supervised and independent settings
* foundational understanding of data management principles for large health-related datasets, with willingness to further develop these skills
* strong skills in research, planning and organisation, computer literacy, effective presentations, and communication

Sponsorship / work rights for Australia

Work rights: candidates must have unrestricted work rights in Australia. Visa sponsorship is not available for this appointment.

Pre-employment checks

Your employment is conditional upon the completion of all role-required pre-employment or background checks satisfactory to the University. Ongoing employment is conditional upon maintaining all relevant clearances and background check requirements. If conditions are not met, the University may take necessary steps including termination of employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander Peoples, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

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