Biostatistician

BIOSTATISTICIAN

QFAB Bioinformatics, Institute for Molecular Bioscience, The University of Queensland

QFAB is a leading bioinformatics facility with a commitment to helping life science and health researchers unlock the full value of their research data. Working closely with researchers, the QFAB team members apply data management, integration, analysis and visualisation techniques to maximise the potential value of large-scale biological and clinical datasets. QFAB is the consulting branch of QCIF, a non-for-profit public company whose members are six Queensland-based universities. This position will be hosted by the Institute for Molecular Bioscience (IMB) at The University of Queensland.

The University of Queensland’s Institute for Molecular Bioscience (IMB) is home to more than 450 scientists, support staff and postgraduate students from more than 40 countries who are working to improve quality of life for all. IMB’s multidisciplinary research programs focus on advancing medical genomics, drug discovery and biotechnology. By investigating the basis of growth and development at the genetic, molecular, cellular and organ level, our researchers aim to better understand the development processes and pathways involved in human and animal health and disease. They also work to translate these findings into diagnostics; technologies and therapeutics to more effectively prevent, detect and treat disease, and deliver a sustainable future for Australia through initiatives such as clean energy and new agricultural compounds.

Details of QFAB Bioinformatics services and IMB research interests may be accessed on the QFAB website at http://qfab.org and the IMB website at: http://www.imb.uq.edu.au

The role

As part of the QFAB team, we are seeking a biostatistician able to work at the interface of molecular biology, medicine and statistics. The role offers an outstanding opportunity to work with leading clinicians and scientists and contribute to cutting-edge research projects in the biological, environmental and medical sciences.

The role involves identifying and gathering analysis requirements from a wide range of life science and clinical researchers and delivering efficient statistical solutions to meet their research outcomes.

The person

Applicants should have expertise in biostatistics applied to clinical research and high-throughput omics studies. In addition to scientific excellence, applicants will have proven success in working with biologists and clinicians. The applicant will demonstrate a high level of personal motivation and initiative with a strong ability to work as part of a team. A high degree of autonomy and professionalism is required to represent QFAB on partners’ premises. Applicants should possess a Masters or PhD degree in statistics or closely related quantitative discipline with at least 3 years of experience in providing statistical expertise in life sciences and medical research.

The University of Queensland values diversity and inclusion.

Applications are particularly encouraged from Aboriginal and Torres Strait Islander peoples. For further information please contact our Australian Indigenous Employment Coordinator at: atsi_recruitment@uq.edu.au

Applications are also encouraged from women.

This role is a full-time or part-time position; flexible working arrangements may be negotiated.

Remuneration

This is a full-time or part-time, one year fixed term appointment at HEW Level 6 or 7. The remuneration package will be in the range $74,207.07 - $79,964.49 p.a. for a HEW level 6 and $81,883.66 - $89,559.15 p.a. for a HEW level 7, plus employer superannuation contributions of up to 17% (total package will be in the range $86,822.27- $93,558.46 p.a. for a HEW Level 6 and $95,803.88 - $104,784.21 p.a. for a HEW Level 7).

Enquiries

To discuss this role please contact Dr Dominique Gorse on +61 7 3346 2624 or d.gorse@qfab.org.

To submit an application for this role, use the Apply button below. All applicants must supply the following documents: Cover letter, Resume and Selection Criteria responses.