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University of New South Wales

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Postdoctoral Fellow in Neuroepidemiology, Dementia and Cognitive Ageing at UNSW University of New South Wales in Australia

Degree Level

Postdoc

Field of study

Data Science

Funding

This is a one-year fixed-term, full-time or part-time employment position commencing in January 2027. Remuneration is Academic Level A6, $118,467 per annum, plus 17% superannuation and annual leave loading. Full-time employment is 35 hours per week; part-time arrangements may be considered at a minimum of 0.6 FTE (three days per week). Benefits include career development opportunities, paid cultural leave, additional Christmas leave and staff discounts.

Deadline

Nov 15, 2026

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Country

Australia

University

University of New South Wales

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Keywords

Data Science
Epidemiology
Psychology
Biostatistics
Longitudinal Study
Statistical Analysis
Alzheimer's Disease
Neuropsychology
Medical Science
Salud Pública
Cognitive Aging
Statistics
Neuroepidemiology

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About this position

The University of New South Wales (UNSW) is recruiting a Postdoctoral Fellow (Data) for the Centre for Healthy Brain Ageing (CHeBA) within the Discipline of Psychiatry & Mental Health in Kensington, Sydney, Australia.

The successful candidate will contribute to research in neuroepidemiology, dementia, cognitive ageing and brain health. Responsibilities include advanced statistical analysis, data preparation and harmonisation, interpretation of complex datasets, and collaboration across international research consortia, longitudinal studies, administrative datasets and multidisciplinary projects.

Applicants must hold a PhD in biostatistics, data science, psychology or a related discipline, together with relevant experience in epidemiology, medical or health research. Strong skills in R, STATA, SAS or SPSS are required, as well as experience with epidemiological or medical-data methods including missing-data imputation, linear mixed models, structural equation modelling or twin-data analysis. An excellent academic record, strong analytical and problem-solving abilities, and scientific writing experience are also expected.

This is a one-year fixed-term position commencing in January 2027. The role may be full-time or part-time, with part-time employment requiring at least 0.6 FTE. Salary is Academic Level A6, $118,467 per annum, plus 17% superannuation and annual leave loading. Visa sponsorship is unavailable, so applicants must have unrestricted work rights in Australia.

Applications, including a resume and selection criteria response, must be submitted online by 15 November 2026 at 11:55 p.m.

Funding details

This is a one-year fixed-term, full-time or part-time employment position commencing in January 2027. Remuneration is Academic Level A6, $118,467 per annum, plus 17% superannuation and annual leave loading. Full-time employment is 35 hours per week; part-time arrangements may be considered at a minimum of 0.6 FTE (three days per week). Benefits include career development opportunities, paid cultural leave, additional Christmas leave and staff discounts.

What's required

Applicants must hold a PhD in Biostatistics, Data Science, Psychology or a related discipline, with demonstrated relevant work experience in epidemiology, medical and health research or a related field. Applicants should have an excellent academic track record; proven experience using R, STATA, SAS or SPSS for epidemiological or medical data analysis; experience with methods such as missing-data imputation, data harmonisation, linear mixed modelling, structural equation modelling or twin data analysis; strong analytical and problem-solving skills; excellent writing skills with experience preparing high-quality scientific papers and technical reports; and a demonstrated commitment to maintaining current discipline knowledge. Candidates must hold unrestricted work rights, as visa sponsorship is unavailable.

How to apply

Submit a resume and selection criteria response through the UNSW online application portal before 15 November 2026 at 11:55 p.m. Applications should be submitted through the portal rather than by email.

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