Research Fellow in Quantum Omics

Responsibilities

• Lead the development, evaluation, and benchmarking of statistical and quantum-inspired methods for high-dimensional omics and cell-based data
• Develop and maintain reproducible research software, workflows, and documentation using robust version control and coding practices
• Collaborate with QUBIC partners and interdisciplinary researchers to translate new methods into applied analyses and usable tools
• Contribute to funding proposals, project reporting, seminars, and conferences to disseminate findings
• Support the supervision of students and junior researchers and engage in School and QUBIC outreach activities

Requirements

• PhD in statistics, computational biology, quantum computing, or a closely related quantitative discipline
• Demonstrated research strength in statistical methods development for high-dimensional omics, ideally including single-cell or cell-based data
• Hands-on experience analyzing large biological datasets, including preprocessing, quality control, and interpretation
• Proficiency with GitHub or similar platforms for version control, with an active profile showcasing code development
• Ability to thrive in multidisciplinary teams and communicate clearly with diverse collaborators

Preferred Qualifications

• Interest or experience in quantum-inspired or quantum computing methods relevant to data analysis and modeling

Benefits

• 17% superannuation
• Flexible work arrangements and progressive leave provisions (including parental, gender affirmation, and cultural leave)
• Career development opportunities and access to tailored leadership programs
• Salary packaging and access to various discounted services
• Health and wellbeing services, including an Employee Assistance Program

About the Company

The University of Melbourne is a leading research institution dedicated to benefiting society through transformative education and research. You will join the Lê Cao Lab within Melbourne Integrative Genomics (MIG) in the School of Mathematics and Statistics, an interdisciplinary center applying advanced mathematics, statistics, and computing to tackle frontier biological questions.