Employer: Garvan Institute of Medical Research

Closing date: This role will remain open until filled. As we will be reviewing applications as they are received, we encourage you to submit yours as soon as possible.

Brief position description: The Opportunity
We are seeking a Research Officer / Senior Research Officer to investigate the earliest steps in cancer initiation and evolution, integrating bioinformatic and population genetic methods. 

Reporting to Professor David Thomas, Laboratory Head – Genomic Cancer Medicine, the key responsibilities include:
• Planning and executing research
• Developing methods to extract quantitative, ultra-low frequency variation from sequence data derived from tumor and blood samples.
• Analysing ultra-low frequency clonal variation in in vitro clonal evolution under selective pressures;
• Applying these methods to quantitate clonal neoplastic events in an extremely cancer-prone population with Li-Fraumeni syndrome; and
• Analysing the whole genomes of more than 20 tumors arising in a cancer-prone family, aiming to identify the common pathways resulting in the formation of tumors in a defined genetic context.

The role will be offered full-time for 2 years in the first instance.

About You
The successful candidate will possess the following key skills and qualifications:
• A PhD in bioinformatics or computational biology, or equivalent experience in a related field.
• Proficiency with genotyping of human samples using massively parallel sequencing technology.
• Ability to manage and process large datasets in a POSIX environment.
• Fluency in at least one scripting language.
• Excellent communication skills and strong in team work and collaborative research
• Ability to conceptualise and execute a research plan to investigate an open-ended question, with minimal supervision.
• A proven track record e.g. publications, grants, software/tool development
• Familiarity with the ethical issues and guidelines relating to the use of human tissue and clinical data for research
• Statistical expertise and experience with the R programming language and key libraries is highly desirable.
• Knowledge of cancer biology and evolution is highly desirable.

Job website: http://garvan.applynow.net.au/jobs/GC201934

Contact name: Human Resources

Contact email: <not provided>