Lecturer in Statistics for Omics
Core
Lead independent research in statistical methods for high-dimensional omics data (genomics, transcriptomics) while teaching statistics and data science at undergraduate and postgraduate levels.
Role type
Academic Lecturer (Research & Teaching)
Builds
Novel statistical methods for complex biological data, high-impact publications, and next-generation researchers.
Domain
Biomedical research / Computational biology / Statistics
Deliverable
production ML models | research | client delivery
Required skills
Statistical methodology, high-dimensional data analysis, genomics/transcriptomics expertise, research grant writing, academic teaching, student supervision
Preferred skills
International collaboration, interdisciplinary work, inclusive academic environment contribution
Technologies
Genomic data tools, Transcriptomics platforms, Statistical computing environments
Responsibilities
Develop novel statistical methods for high dimensional biological data, Publish in leading statistics and computational biology venues, Design and deliver undergraduate and postgraduate subjects, Supervise and mentor honours, MSc and PhD students, Contribute to School, Faculty and MIG leadership and governance
Seniority
Mid-to-Senior level Academic (Lecturer to Associate Professor track)