Post-doctoral Research Fellow

1 month ago


Adelaide, South Australia University of Adelaide Full time
Post-doctoral Research Fellow - Cancer Bioinformatics

We are seeking a highly motivated and experienced post-doctoral research fellow to join our team in cancer bioinformatics. The successful candidate will have a strong background in bioinformatics, AI, or related fields and a proven track record of quality research in relevant fields.

The post-doctoral research fellow will be responsible for leading AI-driven research in cancer bioinformatics, leveraging cutting-edge techniques to unravel complex biological insights. This exciting role involves pioneering AI-driven methods to analyse cancer-related biological data, aiming to uncover novel patterns and mechanisms underlying cancer progression and treatment response.

The successful candidate will have the opportunity to work within a dynamic and collaborative environment, contributing to ground-breaking discoveries with real-world implications for cancer patients. We are seeking a passionate and driven individual with a strong commitment to interdisciplinary research and a track record of successful collaborations.

The University of Adelaide is a uniquely rewarding workplace, offering a wide range of attractive staff benefits, including salary packaging, flexible work arrangements, high-quality professional development programs, and an on-campus health clinic, gym, and other fitness facilities.

We are committed to providing a working environment that embraces and values diversity and inclusion. Female applicants, people with a disability, and/or Aboriginal and Torres Strait Islander people who meet the requirements of this position are strongly encouraged to apply.

  • A PhD in Computational Biology, Computer Science, Artificial Intelligence, or Software Engineering (or equivalent)
  • A record of quality research in relevant fields, as evidenced by publications in leading journals and at conferences commensurate with opportunity
  • Experience in machine learning and deep learning
  • Proficiency in one or more high-level programming languages such as Python, Java, or R
  • Strong commitment to interdisciplinary research and a track record of successful collaborations


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