First listed on: 18 April 2019

Postdoctoral Research Fellow in Spatial Statistics and Machine Learning

The Opportunity

  • Develop innovative concepts and tools to image Earth's structure and its resources.
  • Launch your professional career in a collaborative multi-disciplinary science environment.
  • Pursue strategic research at CSIRO, Australia's leading science and technology organisation.

Australia’s future minerals, energy and water resources will come from greater depths in the onshore regions and from deep offshore plays. Our ability to find, define and exploit mineral resources is limited by a deep and complex regolith that covers about 80% of the Australian land mass. Undiscovered conventional oil and gas lies in deeper or more subtle traps, or else is sourced from unconventional sources onshore that require new geophysical methods to quantify.  The science of Deep Earth Imaging will help us more precisely image and understand the significance of subsurface rock properties, which in turn will unlock the resource potential of this vast and relatively under-explored continent.

As a part of this effort, we seek an outstanding early career researcher with a background in Spatial Statistics and Machine Learning with significant experience in exploratory data analysis and hypothesis generation for geological datasets to join a growing, world-leading team of 25 researchers. The successful candidate will have demonstrated experience in exploratory data analysis and visualization of large spatio-temporal datasets.

Your duties will include

  • Under the direction of a senior research scientists, the successful candidate will conduct innovative research aligned with the goals of Deep Earth Imaging that ideally lead to novel and important scientific outcomes:
  • Develop approaches for intuitive visualisation of large spatio-temporal datasets to allow formulating hypotheses on the underlying data-generating process
  • Develop and apply machine learning algorithms for classification and regression of earth science datasets, with particular emphasis on incorporating expert knowledge in training data set generation
  • Undertake regular reviews of relevant literature and intellectual property.

Location: Kensington, WA

Salary: AU$83,687 - AU$94,679 plus up to 15.4% superannuation

Tenure: specified term of 12 months

Reference: 61371

To be successful you will need

  • A doctorate in a relevant discipline such as geophysics, geology, applied mathematics or statistics

Please note: To be eligible for this role you must have no more than 4 years of relevant postdoctoral experience.

  • Demonstrated experience in exploratory data analysis and visualisation of large spatio-temporal datasets
  • Demonstrated experience in applying machine learning techniques to spatio-temporal problems
  • Demonstrated experience and skill in scientific programming
  • Evidence of high quality written and oral communication skills achieved through high-level reporting, publication, and presentation.
  • Evidence ability to work effectively as part of a multi-disciplinary, research team
  • Motivation and self-discipline to conduct independent research.
  • A record of science innovation and creativity with the ability and willingness to incorporate novel ideas and approaches into scientific investigation.

For details about who to contact and for more information please view the Position Description

We’re working hard to recruit diverse people and ensure all our people feel supported to do their best work and empowered to let their ideas flourish.

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


At CSIRO you can be part of helping to solve big, complex problems that make a real difference to our future. We spark off each other, learn from each other, trust each other and collaborate to achieve more than we could individually in a supportive, rewarding, inclusive and truly flexible environment.

Apply Online

To apply online, please provide a CV and cover letter outlining your suitability and motivation for the role.

Applications Close 

Thursday May 16th, 2019

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