• Join CSIRO’s Deep Earth Imaging Future Science Platform
• Utilise your expertise in geostatistics in the study of resource prospectivity
• Develop and apply methods to probabilistically map resource potential for minerals

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.  Deep Earth Imaging science 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.

We seek an outstanding early career researcher who has demonstrated excellence in geostatistics and its applications in earth sciences, machine learning and probabilistic methods that could be applied to resource prospectivity studies. The successful candidate will develop and apply methods to probabilistically map resource potential for minerals, with possible extensions to perform similar studies for energy and water resources.

This role would involve the development of a research plan to implement Deep Earth Imaging's vision for 21st century holistic exploration tools; the researcher would also be responsible for utilising the research of postdoctoral research fellows to study resource potential.

Under the direction of senior research scientist(s) in the Deep Earth Imaging Future Science Platform and CSIRO Mineral Resources, the successful candidate will conduct innovative research aligned with the project goals, producing novel and important scientific outcomes:

• Develop and apply geostatistical methods to assist study of resource prospectivity;
• Develop and apply novel machine learning tools to heterogeneous geoscience data; and
• Develop new tools and techniques to assist in probabilistic mapping of resource potential.

Term: 3 years
Salary: $95k to $103k plus up to 15.4% super
Location: Kensington, WA
Reference Number: 56188

The successful candidate will have:

1. A doctorate in a relevant discipline such as geology or statistics with a focus on geostatistics or machine learning, and at least two years post-PhD experience in the application of geostatistics, machine learning to earth science problems.
2. The ability to demonstrate, through a 1-2 page research plan as part of their application, an ability to plan research aligned to the vision of Deep Earth Imaging.
3. Experience in a wide range of geostatistical approaches to simulate spatially variable fields, such as lithology, earth properties or fault networks.
4. Demonstrated experience and skill in machine learning and/or scientific programming.

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 do this by using science and technology to solve real issues. Diversity is the compass that navigates our innovation. We provide an inclusive workplace that respects, values and actively pursues the benefits of a diverse workforce.  

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 Balance

How to Apply:  Candidates should develop a 1-2 A4 page research plan outlining their concepts for research they would like to undertake in this role should they be successful. Candidates should show how they can meet the research vision of Deep Earth Imaging.

If you wish to apply for this position, please upload 1 document only containing your covering letter, research plan and resume that best demonstrates your ability to meet the requirements of the role.   

Before you apply please view the full position description and selection criteria here:  PD

Applications Close:  11:59pm AEDT, Monday April 9th 2018