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. In their role as ANU academic level B in the School of Computing, the appointee will be expected to: 1. Undertake research in the area of the HMI project, independently and as part of a team, with a view to publishing original and innovative results in refereed conferences and journals, present research at academic seminars and at national and international conferences, and collaborate with other researchers at a national and/or international level. 2. Seek and secure external funding including the preparation and submission of research proposals to external funding bodies. 3. Contribute, at a reduced intensity relative to a standard faculty appointment, to the teaching activities of the School at the undergraduate and graduate levels. This includes, but is not limited to, the preparation and delivery of lectures and tutorials, the preparation of online material, marking and assessment, consultations with students, acting as subject coordinators and the initiation and development of course/subject material. 4. Supervise students working on individual or group projects at undergraduate, honours, graduatecoursework levels. Assist with supervision of research students. 5. Contribute to the operation of the School. 6. Assist in outreach activities. 7. Maintain high academic standards in all endeavours. 8. Take responsibility for their own workplace health and safety and not willfully place at risk the health and safety of another person in the workplace. 9. A demonstrated understanding of equal opportunity principles and policies and a commitment to their application in a university context. 10. Other duties as required consistent with the classification level of the position.
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. SELECTION CRITERIA: 1. A PhD or close to completing a PhD in Computer Science, Artificial Intelligence, Robotics, or allied discipline relevant to the HMI project (economics, engineering, mathematics, philosophy, political science, statistics, sociology) with a track record of independent research in one or more of the following fields: Automated planning, including motion planning and multi-agent planning, robotics, machine learning, algorithmic game theory, or robust control, as evidenced by publications in peer-reviewed conferences and journals, a record of developing and maintaining collaborations, and other indicators of peer recognitions, such as awards. 2. Evidence of the ability to articulate and execute innovative research in ethical AI/ML/robotics, or closely related topic relevant to the HMI project. 3. High proficiency in computational techniques and programming. 4. Demonstrated ability to work cooperatively and harmoniously in a team, with the capacity to engage in crossdisciplinary research and build a research community. 5. An ability and commitment to assist bids for competitive external funding to support individual and collaborative research activities. 6. Ability and willingness to teach at all levels, though with reduced intensity relative to standard academic appointment. 7. The ability to assist in supervising PhD / Master research students 8. Excellent oral and written English language skills and a demonstrated ability to communicate and interact effectively with a variety of staff and students in a cross-disciplinary academic environment and to foster respectful and productive working relationships with staff, students and colleagues at all levels. 9. Commitment to upholding the University’s values and outstanding personal qualities of openness, respectfulness, and integrity, including a demonstrated understanding of equal opportunity principles and policies and a commitment to their application in a university context.
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.
Canberra ACT We strongly encourage and support applications from First Nations people for this role. HOW TO APPLY: 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. For further information please contact Hanna Kurniawati: [email protected] Applications close: 12 May 2021 11:55:00 PM AUS Eastern Standard Time