Children's Medical Research Institute (View other jobs from this organisation)
Children’s Medical Research Institute (CMRI) was Australia’s first dedicated paediatric research facility and is now one of the nation’s most highly regarded independent medical research centres. Our research focuses on the areas of embryonic development and birth defects, cancer, neuroscience and gene therapy and we have a strong international reputation based on our research outcomes. CMRI’s research programs are supported by state of the art facilities and committed research and support staff. Our achievements are made possible by a loyal network of community supporters, highly engaged donors and the very successful Jeans for Genes® fundraising campaign.
A Biostatistician position is available in the ProCan Cancer Data Science Group, led by Dr. Qing Zhong. ProCan (the ACRF International Centre for the Proteome of Human Cancer) is a world-first initiative developed and launched in September 2016 by Professors Phil Robinson and Roger Reddel, and established with a $10 million grant from the Australian Cancer Research Foundation (ACRF). Equipped with six SCIEX mass spectrometers and a super computer (800TB / 480 cores), ProCan processes tumour samples through a proteomic method, SWATH-MS, which allows fast mass spectrometric conversion of small amounts of tissue (biopsy level) into a single, permanent digital file representing the quantitative proteome of the sample. ProCan’s aim is to measure thousands of proteins in 70,000+ samples of all types of cancers with known treatment outcome and correlate cancer proteotypes with clinical phenotypes. ProCan is the lead in a proteogenomics consortium that has signed the first Memorandum of Understanding with the United States National Cancer Institute, as part of the Cancer Moonshot Initiative.
The Cancer Data Science Group aims to develop novel computational tools and sophisticated machine learning algorithms to achieve this goal. Other major focuses of the group are 1) big proteogenomic data mining and management, 2) the genome-proteome association analysis and multi-omic data integration for studying cancer, 3) development of advanced statistical tools to account for batch effects caused by large-scale, high throughput mass spectrometry-based proteomics, and 4) implementation of big data-driven, evidence-based computational tools to achieve predictive, preventive, personalized medicine.
We invite applications from PhD scientists to join our group. Applicants should have a high degree of motivation in academic research, an excellent record of scientific accomplishments with publications in peer-reviewed journals, and the ability to work independently with outstanding communication and writing skills. Candidates should have a strong background in biostatistics or statistics and be interested in cancer-related genomics and proteomics. Knowledge in biostatistics, applied statistics, and computational modelling is essential. Strong programming skills in R and Python are required. Previous experience in proteomics would be helpful, but not essential. You will be responsible for conducting biostatistical analysis, performing survival analysis, developing solutions to problems such as batch effects, missing values and FDR in the current proteomics research.
You will be provided with a competitive remuneration package in accordance with qualifications and experience. Additional benefits include the provision of a Public Benevolent Institution salary packaging scheme and participation in an employer-contributed superannuation fund. This is a full-time position for two years with the possibility of extension.
Applications should include:
- A cover letter(citing PV2004) with statement of motivation and a detailed description of the qualifications described above,
- A curriculum vitae including a chronological list of publications
- Contact details (phone/email) of three professional referees and be forwarded to firstname.lastname@example.org
Applications will remain open until filled, however we encourage you to submit your application by 21st February as we will interview suitable candidates from that date onwards - We reserve the right to withdraw this ad prior to the closing date.
- Closing Date:
- 21 Feb 2020
- Work Type:
- Full Time