Postdoctoral/Research Fellow, ANU College of Engineering and Computer Science

5 days left

Location
Canberra, Australia
Posted
08 Apr 2021
End of advertisement period
12 May 2021
Ref
539979
Contract Type
Fixed Term
Hours
Full Time

Classification: Academic Level A-B
Salary package:

  • Academic Level A $73,309 to $92,015 plus 17% superannuation
  • Academic Level B $99,809 to $113,165 plus 17% superannuation

Terms: Full time, Fixed Term (2 years)

  • Opportunity to design and develop fundamental approaches for decision-making and learning in non-deterministic and partially observed scenarios, including in adversarial scenarios.
  • Opportunity to apply the above techniques to one or more realistic robotics problems, in collaboration with our external partner(s).

 Position overview

The ANU College of Engineering and Computer Science (CECS) is one of the premier engineering and computer science research institutions in the world. It comprises of the School of Computing, School of Engineering and School of Cybernetics. The first two school are recognised as research leaders in multiple areas, including in Artificial Intelligence, Machine Learning, and Control. These two schools will continue their tradition of excellence in research, while the School of Cybernetics is an exciting new school in pursuit of understanding the societal aspects of computing and robotics.

The School of Computing is seeking a Postdoctoral Research Fellow to focus on robot planning and learning in partially observed and adversarial scenarios. The school is a community of high performing academic and professional staff, students and visitors sharing a deep commitment to transforming the future of computing for the next generation. It is a leading centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing.

The successful candidate will have completed, or nearly completed a PhD in Computer Science or related area with a focus on one or more of the following fields: Planning under Uncertainty, Motion Planning under Uncertainty, Multi-Robot Planning under Uncertainty, Reinforcement Learning, Markov Decision Processes, Partially Observable Markov Decision Processes, Algorithmic Game Theory, or Robust Control. Experience in applying research results from one of the mentioned areas to a physical robot is a plus.

For further information please contact Hanna Kurniawati E: hanna.kurniawati@anu.edu.au

Closing Date: 12 May 2021

Position Description: Download FileAcademic Level B_Research Fellow - v3.pdf

We welcome and develop diversity of backgrounds, experiences and ideas and encourage applications from individuals who may have had non-traditional career paths, who may have taken a career break or who have achieved excellence in careers outside of the higher education sector. We support applicants who require flexible arrangements in their work environments or patterns. If your experience looks a little different to what we’ve described, but you’re passionate and motivated by this position, we welcome your enquiry and application.

ANU values diversity and inclusion and is committed to providing equal employment opportunities to those of all backgrounds and identities. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion

Application information

In order to apply for this role please make sure that you upload the following documents:

  • A statement addressing the selection criteria, please identify clearly which level you are applying for.
  • A current curriculum vitae (CV) which includes the names and contact details of at least three referees (preferably including a current or previous supervisor). If your CV does not include referees you can complete these online when prompted in the application form.
  • Other documents, if required.

Applications which do not address the selection criteria may not be considered for the position.

The successful candidate will be required to undergo a background check during the recruitment process. An offer of employment is conditional on satisfactory results

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