http://federal.governmentcareer.com.au/
The Position
Data61 is offering an exciting opportunity for a Researcher to join its Machine Learning Research Group (MLRG). We are seeking talented researchers with core expertise in causal inference, reinforcement learning, deep learning, convex optimization, non-parametric Bayesian analysis.
You will be working in the MLRG, a group with expertise in core ML methods that spans a wide area of computer science and applied mathematics. You will also collaborate with experts in related fields (including statistics, computer vision, natural language processing, etc.).
You will be solving real-world problems and be contributing to foundational work on core ML. You will be pushing the boundaries of the state of the art on challenging ML projects the MLRG is involved in along with major stakeholders.
Data61 is the largest data innovation group in Australia, bringing together approximately 600 research staff, including a strong 300+ PhD student program in collaboration with the best universities across Australia. We provide flexible working hours, ownership of projects, freedom to experiment with new technologies and the ability to learn and grow to your full potential.
Location: Canberra, ACT or Sydney, NSW
Salary: AU $97K to AU $105K plus up to 15.4% superannuation
Tenure: Specified term of 3 years
Reference: 57800
To be successful you will need:
Before applying, we encourage you to read the full position description for this role. This document can be viewed at:
Who we are: The Commonwealth Scientific and Industrial Research Organisation (CSIRO)
At CSIRO, we do the extraordinary every day. We innovate for tomorrow and help improve today - for our customers, all Australians and the world. We imagine. We collaborate. We innovate.
We work flexibly at CSIRO, offering a range of options for how, when and where you work. Talk to us about how this role could be flexible for you. Find out more! CSIRO Balance
How to Apply: To apply, please provide a CV as well as a cover letter addressing the selection criteria in brief, and upload these as one document. If your application proceeds to the next stage you may be asked to provide additional information.
Applications Close: Open until filled.