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« Systems biology and software development (Postdoc or Research Engineer/Scientist) - CSIRO | Main | PhD Scholarships - University of Queensland Diamantina Institute »

PhD Scholarships in Computational Biology - University of New South Wales

We are seeking candidates with a strong academic record to undertake PhD studies with the Complex Systems in Biology and Computational Biology groups at the University of New South Wales. The successful candidates will join a team of researchers in the Complex Systems in Biology and Computational Biology Groups that use mathematical, computational, bioinformatics, and statistical approaches to study various aspects of the immune system and immune responses to a variety of infectious diseases. This research is done in collaboration with world-class experimental research groups both in Australia and overseas. The groups have a high publication output and a strong history in successful interdisciplinary training. It is an ideal venue for scientists considering a career change from other quantitative disciplines to work in mathematical / computational biology.

For more details about the research groups and their research interests:

The scholarships provide an annual tax-exempt stipend of $25,000 commencing in semester 1 of 2013 for three years full time and will be awarded on a competitive basis. To candidates with an Australian Postgraduate Award (APA) or similar scholarship award, we offer a top up of at least $8,000 per annum. These scholarships are for study at the University of New South Wales in Sydney, Australia.

More information on the UNSW postgraduate research scholarships is available at:

The research projects are suited to students with a strong background in a quantitative discipline such as bioinformatics, computer science, mathematics, statistics, physics, or engineering. Acceptance is competitive, with a first class honors degree (or equivalent) and a GPA of >87% required.

Expressions of interest should be directed to

Please include a cover letter and CV that provide details about previous employment history (if any), education history, technical skills, and research interests.