Research Fellow, School of Computing

Location
Canberra, Australia
Posted
Tuesday, 13 April 2021
End of advertisement period
Wednesday, 12 May 2021
Ref
540003
Contract Type
Fixed Term
Hours
Full Time

Classification: Academic Level B
Salary package: $99,809 - $113,165 plus 17% superannuation
Terms: Full time, Fixed Term, 2 years.

  • Opportunity to design novel approaches for decision-making and learning, with an application to develop robust and strategically empathetic robots.
  • Opportunity to join a major cross-disciplinary research project, the ANU Humanising Machine Intelligence (HMI).
  • Opportunity to leverage a variety of expertise in decision-making under uncertainty, to develop novel approaches in robust decision-making and learning for robots. 

Position overview

The HMI is a major cross-disciplinary project at the ANU, uniting a team of computer scientists, philosophers, and social scientists in the pursuit of a more ethical future of machine intelligence. We share a common expertise in probabilistic decision-making, though coming from different perspectives. Such a multi-disciplinary background provides a holistic view of automated decision-making that the team, including the to be appointed Research Fellow, can leverage.

The Research Fellow position will be based at the ANU’s School of Computing and collaborate closely with team members within and across discipline to make substantial progress towards ethical AI. 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, Artificial Intelligence, Robotics, or  disciplines relevant to the HMI project with experience in one or more of the following fields: Planning under uncertainty, motion planning under, multi-agent planning, robotics, reinforcement learning, robust control, or algorithmic game theory. 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: hanna.kurniawati@anu.edu.au.

Closing Date: 12 May 2021

Position Description: Download File Academic Level B_Research Fellow - HMI - v2 (1).pdf

We strongly encourage and support applications from First Nations people for this role.

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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