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« Senior Bioinformatician & Bioinformatician - South Australian Health & Medical Research Institute (SAHMRI) | Main | Postdoctoral position in cardiac cell systems biology »

Postdoctoral Bioinformatician - Peter MacCallum Cancer Centre

Applications are invited for a new research position based within the Cancer Genetics and Genomics laboratory (Bowtell laboratory) of the Research Division at the Peter MacCallum Cancer Centre. The Bowtell lab is a leading Australian human cancer genomics group and a major contributor to ovarian cancer research internationally. This project focuses on understanding the genomic landscape of high-grade serous ovarian cancer and how mutations lead to treatment response and resistance. This work has direct clinical application, and the Bowtell lab has a strong reputation for translational findings in ovarian cancer.

The position will involve the analysis of large-scale genomic data through the application of best-practice bioinformatics workflows and the development of innovative methods as required. The position will require a highly motivated and skilled bioinformatician or computational biologist with expertise in the analysis of cancer whole genome sequencing and RNAseq data, integration of genome-wide datasets, competency in programming languages R and/or Python/Perl and experience with working on a high performance-computing cluster. The individual will collaborate very closely with cancer cell and molecular biologists within the Bowtell laboratory to work on joint initiatives but will also be responsible for driving their own specified biological projects. The position is in a research environment that includes a large and interactive group of bioinformaticians and computational biologists in the Bioinformatics Core Facility.


  • A PhD in Bioinformatics, Computational Biology, or a quantitative discipline (e.g. computer science, mathematics, or statistics) with very good biology knowledge
  • Demonstrated experience in the analysis of Illumina next-generation sequencing data, DNA copy number and RNA sequencing analysis methods
  • Excellent knowledge of R language and tools available from the bioconductor project for high throughput genomic data analysis

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