Position title: Computational genomics and statistics

Employer: The University of Melbourne

Closing date: 22 October 2020

Brief position description: The School of Mathematics and Statistics (https://ms.unimelb.edu.au), and its partner Melbourne Integrative Genomics (MIG, https://research.unimelb.edu.au/integrative-genomics) are seeking a qualified and enthusiastic Research Fellow to lead cutting-edge research in method development, implementation and analysis of biological data.
The position will be based at MIGand will report to A/Prof Kim-Anh Lê Cao, whose lab specialises in the development of computational methods for cutting-edge ‘omics data (https://lecao-lab.science.unimelb.edu.au). The successful incumbent will work closely with our collaborative network across the campus, including the biomedical and computational biology precinct: Walter and Eliza Hall Institute of Medical Research (https://www.wehi.edu.au), the School of Biomedical Sciences (Centre for Stem Cells Systems) as well as external Australian and international institutions (France, Canada). A/Prof. Lê Cao lab’s research combines statistical modelling, computational frameworks and ‘omics data analysis, including but not limited to transcriptomics and epigenomics at the single cell level and metagenomics, to obtain a holistic understanding of a biological system in a healthy or disease state. We are interested in a range of analysis frameworks, such as unsupervised, supervised and longitudinal.
The position offers a rare opportunity to work in a multi-disciplinary environment amongst statisticians, bioinformaticians and biologists. The successful applicant will be highly skilled in R programming, will have an excellent understanding of the context in which biological data arise, and will be an excellent team player with the ability to mentor other team members. The successful applicant will be highly encouraged in developing their own research career path and research directions. An opportunity to teach some postgraduate lectures at the University within the incumbent’s expertise area is also offered.

Job website: http://obs.unimelb.edu.au/caw/en/job/898848/research-fellow-computational-genomics-statistics

Contact name: Kim-Anh Le Cao

Contact email: kimanh.lecao@unimelb.edu.au