CSIRO Postdoctoral Fellowship in Machine Learning for Robotic Mobility

Commonwealth Scientific & Industrial Research Organisation (CSIRO)

Pullenvale, Brisbane, Australia

ID: 7054469 (Ref.No. 58909)
Posted: November 22, 2018
Application Deadline: Open Until Filled

Job Description

• Excellent development opportunity working on high-profile projects
• Contribute to research enabling robots to traverse novel terrains
• Help shape the future at Data61, Australia’s leading data innovation group

The Opportunity:

CSIRO Postdoctoral Fellowships help facilitate the recruitment and development of our potential leaders. They provide valuable opportunities for scientists and engineers to launch their careers, extend professional networks and enhance their career prospects.

As the CSIRO Postdoctoral Fellow in Machine Learning for Robotic Mobility with CSIRO’s Data61, you will undertake research enabling mobile robots to traverse novel environments/terrains. You are an experience-based learner who can pick up new concepts and skills quickly, and you are able to generalise that experience in extended missions. This may involve creating novel mappings from sensors to learned metric-spaces, and using a robot’s experience (e.g. hitting a rock) to generalize and avoid related situations (rocks or stumps in road). You will be hands on with legged and wheeled vehicles; developing new robotic behaviours, and working within larger teams developing these platforms.

The Robotics and Autonomous Systems group is competing in the systems track of the DARPA SubT Challenge and it is expected that this Postdoctoral Fellow will contribute to this Challenge project. Join our team and be part of this exciting initiative involving the creation of fast capable robots traversing novel complex terrain.

Your duties will include:

• The creation of novel software models and algorithms.
• Reviews of relevant literature and patents.
• Producing scientific and/or engineering papers for publication.
• Preparing and presenting conference manuscripts.
• Contributing to the development of innovative concepts and ideas for further research.

Location: Queensland Centre for Advanced Technologies (QCAT)
Pullenvale (Brisbane) Queensland, Australia
Salary: AU $85k – AU $93k per annum, plus up to 15.4% superannuation
Tenure: 3 year term
Reference No.: 58909

To be considered you will need :

• A doctorate in a relevant discipline area, such as computer science, robotics, electrical, mechanical or mechatronic engineering.
• Less than three years of relevant research experience since completing your PhD.
• The ability to communicate well both verbally and in writing, and a history of professional behaviours.
• A record of applying machine learning to perception or robotics problems, or published fundamental contributions in machine learning
• At least, a strong desire to work hands-on with robotic systems.
• The ability to work well in a team environment, as well as autonomously.
• A record of science innovation and creativity.

To see all the criteria required for success in this role, click on the ‘Position Details’ link on the ad at CSIRO Careers - https://performancemanager10.successfactors.com/xi/ui/rcmjobreq/pages/jobReqProfile.xhtml?s.crb=KVVZwUprEEgpdn7Bl0Nn4Kce3AE%3d&jobReqId=58909.

To be eligible for this postdoctoral fellowship, you will have less than 3 years (or part-time equivalent) of relevant research experience since gaining your PhD.

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.

CSIRO’s Commitment to Diversity: 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.

Work-Life Balance: 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.

To apply online, please visit:


Next, upload a CV and cover letter outlining your suitability for the role and your motivations for applying.

Applications will remain open until filled.


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