Employer: Walter and Eliza Hall Institute of Medical Research
Closing date: 6 June 2024
Brief position description:
An exciting opportunity exists for a talented and motivated computational scientist to join a new research program developing and applying artificial intelligence and machine learning methods to analyze biomedical molecular data from cancer and other diseases at Australia’s pre-eminent biomedical research institute.
About the position
Recognizing the emerging importance of artificial intelligence and machine learning in biomedical research, WEHI is investing strongly in a new research program and is creating multiple new AI Research Fellow positions.
This position will be based in the Papenfuss Laboratory within the Computational Biology Theme. It will involve developing and applying machine learning techniques to integrate large-scale bulk, single cell or spatial omics data to identify disease subtypes and predictive biomarkers in a variety of health-related settings, including infectious disease and cancer. There will be opportunity for methods development and to collaborate widely in the application of AI to molecular data at WEHI.
The successful candidate will join a growing interactive team of computational scientists in a supportive and flexible working environment. They will work alongside other AI and machine learning experts as part of a broader AI research community developing at WEHI. The research is well-supported by state-of-the-art computing facilities and engineering expertise.
The successful candidate will have a PhD in a quantitative discipline such as Computer Science, Bioinformatics, Computational Biology, Mathematics, Statistics or Physics, together with expertise in machine learning techniques applied to multi-omics data.
The level of appointment will be in the Research Officer or Senior Research Officer band, depending on the candidate's experience. The position is available for a period of 3 years in the first instance with the possibility of renewal. Up to 17% superannuation and very attractive salary packaging options are available.
Selection Criteria
Personal:
A PhD in Bioinformatics, Computational Biology, Computer Science, Mathematics, Statistics or Physics demonstrated through publications or a thesis
A collegiate approach and interest in collaboration
Good time management skills
Excellent skills engaging with and managing collaborators and stakeholders
Knowledge and skills:
Expertise in omics analysis and machine learning or artificial intelligence
Experience with genomic, transcriptomic or other high-throughput data
Experience applying machine learning techniques to biological data
Strong data analysis skills using unix and languages such as R or python
High-level data management skills
Highly developed written and verbal communication skills
Contact name: Tony Papenfuss
Contact email: papenfuss@wehi.edu.au