CSIRO Postdoctoral Fellowship in ML/AI FSP: Classifying Radio Galaxies in Large Surveys

Last updated 1 hours ago
Location:Perth
Job Type:Full Time

The Opportunity
  • Do you have a PhD in computing, astrophysics or physics?
  • Work with World-leading scientists & engineers on machine learning solutions for astronomy
  • Join CSIRO - Australia's premier science and technology research organisation

CSIRO Early Research Career (CERC) Postdoctoral Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years of relevant postdoctoral work experience. These fellowships aim to develop the next generation of future leaders of the innovation system.

Future Science Platforms (FSPs) are a major CSIRO initiative. FSPs are multi-year investments in frontier science that will reinvent and create new industries for Australia.

CSIRO Astronomy and Space Science (CASS) and FSP are joining together to appoint a Postdoctoral Fellow in Machine Learning and Artificial Intelligence (ML/AI) to work with world class scientist to classify radio galaxies in large surveys. As the successful candidate, you will work at the interface of astrophysics and machine learning to enable cutting edge astrophysics.

Your duties will include:
  • Develop machine learning methods for identifying the morphology of radio galaxies in ASKAP data, cross-match them with optical/infrared images, and extract galaxy properties.
  • Implement these methods efficiently on high performance computing systems.
  • Carry out evaluation of the developed software to demonstrate its competitiveness and fitness for purpose. Taking responsibility for functionality, performance and robustness.
  • Carry 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.
  • Collaborate with members of a diverse project team and external partners to ensure research directions can lead to lasting impact in application domains.

Location: Kensington, Perth WA Australia
Salary: AU$83k – AU$94k plus up to 15.4% superannuation
Tenure: Specified term of 3 years
Reference: 67033

To be considered you will need:
  • A doctorate (or will shortly satisfy the requirements of a PhD) in a Platform-relevant discipline area, such as computing, astrophysics or 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.
  • A sound history of publication in peer reviewed journals and/or authorship of scientific papers, reports, grant applications or patents.
  • Solid knowledge of machine learning techniques and proven ability to develop and apply novel machine learning techniques to complex data sets.
  • The ability to work effectively as part of a multi-disciplinary, regionally dispersed research team, plus the motivation and discipline to carry out autonomous research.
  • Knowledge of Python, Julia, C, C++ or equivalent.

For full details about this role please view the Position Description

Eligibility

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

Flexible Working Arrangements

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

Diversity and Inclusion

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.

About CSIRO

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

Join us and start creating tomorrow today!

How to Apply

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.

Applications Close

Sunday 21 June 2020, 11:00 pm AEST