Academic Level A or Research Assistant level 5/6
Sydney School of Public Health
We are seeking expressions of interest for the position of Biostatistician to join our research team. This position will contribute statistical analyses to a range of projects on topics related to chronic kidney disease and solid organ transplantation, at the Centre for Organ Donation Evidence https://organdonationevidence.org.au/
Projects will include, for example, predicting donation and transplantation outcomes, modelling changes in the epidemiology of morbidity and mortality, using national linked health datasets, and diffusion of new treatment technologies for chronic kidney disease in Australia using national registry data, and on comparing treatment options for people with diabetes and kidney failure in Australia and New Zealand. The role will include work on a several large data linkage projects which have either been achieved or are in process.
The successful applicant will be responsible for applying a variety of statistical methods to project data, including survival analyses, regression modelling, excess mortality modelling, risk prediction modelling and statistical methods for analysing correlated data. The applicant will be required to generate reports for stakeholder meetings, and other dissemination, as well as contribute to academic papers.
This is a research only position, based at Sydney School of Public Health. The successful applicant will work closely with Professor Angela Webster, clinical epidemiologist and transplant nephrologist, and Dr Nicole De La Mata, biostatistician. Training will be provided, and there will be opportunity to develop data management specialist skills, and to attend academic conferences to present project work. The successful applicant will be expected to make an active contribution to papers and new grant submissions arising from this work.
The successful applicant will have a minimum Masters or equivalent degree in statistics, biostatistics or other quantitative discipline and will have strong, demonstrated skills in statistical analysis of complex clinical or epidemiological data. Candidates without these qualifications but who have demonstrated experience may also be considered. We prefer to work in Stata or R, but knowledge of SAS and other relevant statistical packages is desirable. The successful applicant will also have excellent communication and interpersonal skills.
This position is offered up to full-time, fixed term (35 hours per week) and is available for 24 months, with the possibility of renewal. For the right candidate, part time or scaled hours will be considered.
Please direct any enquiries to Angela Webster, on firstname.lastname@example.org or Nicole De La Mata, email@example.com with details of experience and qualifications by Monday 19th September 2022.