• Use high level computational/programming skills to build machine learning models
• Be part of the team building the next generation of science tools
• Work with leading MLAI scientists as part of our Future Science Platform 

Your research will focus on applying Machine Learning and Artificial Intelligence to the analysis of sample material data sets and in the design of the experiments as part of a data driven science initiative to accelerate material optimisation workflows.  Themes that will be explored include the use of Machine Learning and Artificial Neural Networks for Materials Science Characterisation data sets, Hybrid Prediction, Decision making, Hyperspectral mapping, Data Visualisation, Design of Experiments and Dimensionality reduction. Solving these types of challenges will open new vistas of scientific knowledge and positive impact in fields such as polymer science, flow chemistry and battery science. This will be done within national and international settings, and as part of a diverse multidisciplinary team.

• Developing and implementing machine learning or artificial intelligence expertise as applied to both the analysis of material sample data sets, as well as in the design of the experiments as part of a data driven science initiative to accelerate material optimisation workflows.
• Implementing these methods efficiently on CSIRO specific high throughput testing systems including robotic synthesis and analysis platforms, and in the domain of flow chemistry.
• Carrying out evaluation of the developed software to demonstrate its competitiveness and fitness for purpose, taking responsibility for functionality, performance and robustness.
• Actively participating in experimental based research program, including sample preparation and analysis.
• Carrying out high impact research of strategic importance to CSIRO, with the aim of achieving innovative and wide-reaching scientific outcomes and ideas for further research.

Location: Clayton, Victoria
Salary: AU$86k - AU$94k plus up to 15.4% superannuation
Tenure: Specified term of 3 years
Reference: 67629

• A doctorate (or will shortly satisfy the requirements of a PhD) in a platform-relevant discipline area such as machine learning, artificial intelligence, computer science, statistics, data analytics, applied mathematics or applied physics.
  Please note: To be eligible for this role you must have no more than 3 years (or part-time equivalent) of postdoctoral research experience.
• Solid knowledge of machine learning, artificial intelligence, and statistics, and the ability to understand and develop mathematically-founded machine learning algorithms and their development in toolkits such as TensorFlow, PyTorch or mlpack.
• High level computational and programming skills (in Python, R, or C++) to build machine learning models and conduct analyses.
• A sound history of publication in peer reviewed journals and/or authorship of scientific papers, grant applications or patents.

For full details about this role please review the Position Description

The successful applicant will be required to obtain and provide a National Police Check or equivalent.

Applicants must be Australian/New Zealand citizens, Australian permanent residents or Australian temporary residents currently residing in Australia and be able to commence in the role by December 2020/January 2021.

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. Balance

We are working hard to recruit diverse people and ensure that all our people feel supported to do their best work and feel empowered to let their ideas flourish. Diversity and Inclusion Strategy

We are committed to the safety and wellbeing of all children and young people.

At CSIRO, Australia's national science agency, we solve the greatest challenges through innovative science and technology.

Join us and start creating tomorrow today!

Please apply on-line and provide a cover letter and CV that best demonstrate your motivation and ability to meet the requirements of this role.

16 August 2020, 11:00pm AEST