Research Fellow/Fellow, College of Engineering and Computer Science

Classification: Academic (Level B/C)
Salary package: Level B: $98,009 - $111,365 plus 17% superannuation Level C: $118,044 - $131,402 plus 17% superannuation
Terms: Full time, Fixed term (3 years, with a possibility of extension to 5 years)

  • Be part of a high-performing project team of 10 CIs and 6 other postdocs attacking the challenge of humanising machine intelligence.
  • ANU, the place to be: #1 in Australia and in the World's Top 25
  • Live in one of the cities with the highest quality of life and one of the most enjoyable to visit

Position Overview

The ANU has launched a major new project on Humanising Machine Intelligence, uniting computer scientists, philosophers, and social scientists in the pursuit of a more ethical future for MI.

Machine intelligence is already used in many applications that, while not explicitly morally-loaded, have clear and profound social implications, from facial recognition, to the distribution of online attention. It is also used to support decisions that have explicit moral dimensions, for example about how to allocate welfare resources, and whom to grant bail or parole. And the application of MI in fully autonomous decision-making systems (robotic and otherwise) is accelerating. Self-driving vehicles, autonomous weapons systems, and companion robots are the first wave of such systems; many more are on the way. Many companies and governments are heavily invested in developing more general, multipurpose forms of MI. All of these autonomous systems will need to be able to make morally-loaded decisions by themselves.

In each of these fields inadequate attention to ethics in the design of MI systems will predictably have negative social consequences, some of which could be catastrophic. The goal of the HMI project is to forestall those risks, and help to realise the tremendous social benefits promised by MI.

The project has three components:

  1. Discovery: formulate the design problem by identifying the social risks and opportunities of widespread reliance on MI.
  2. Foundations: identify and answer the fundamental theoretical questions on which progress towards ethical MI depends.
  3. Design: develop ethical algorithms and broader MI systems in partnership with industry and government.

The HMI project chief investigators are: Associate Professors Seth Lazar (Project Leader), Colin Klein and Katie Steele (Philosophy), Professors Marcus Hutter, Sylvie Thiébaux, Bob Williamson and Lexing Xie (Computer Science), Dr. Jenny Davis (Sociology), Associate Professor Idione Meneghel (Economics), and Professor Toni Erskine (Political Science).  We have already appointed 6 postdoctoral researchers in a range of areas relevant to the project, and are now looking for someone with a machine learning or related background interested in the ethical dimensions of this technology.

Our primary criterion for this position is demonstrated research excellence and the clear potential to be research leaders in the field of moral MI. Successful applicants will also be ready and equipped to engage with scholars from other disciplines and are expected to work actively with scholars from at least two of the project’s discipline areas.

The successful applicant will help us design the next generation of more ethical MI systems, in part through publishing internationally influential research in the leading peer-reviewed venues (as suited to their discipline). We expect them to become leaders in academia, industry or government. As well as conducting research at the highest level, they will help build the HMI community at ANU and globally, through convening a regular seminar series and international workshops. They will also contribute, at a reduced intensity, to the education and outreach agendas of the School, in a manner appropriate to the level of appointment.

The position is available at academic Level B (Research Fellow) or C (Senior Fellow) and is for an initial duration of 3 years with the potential for extension to 5 years following a mid-term project review. For candidates who currently hold tenure-track or permanent appointments at universities, industry or government and in other exceptional circumstances, a tenure-track or continuing appointment may be considered.

The ANU provides attractive benefits and excellent support to maintain a healthy work/life balance and offers generous remuneration benefits, including four weeks paid vacation per year, assistance with relocation expenses and 17% employer contribution to superannuation. This also includes generous parental leave, the possibility of flexible and part time working arrangements, a parental and aged care support program, dual career hire programs, ANU school holiday programs, and childcare facilities on campus. For more information, please visit https://services.anu.edu.au/human-resources

For further information please contact, Professor Bob Williamson,

E: bob.williamson@anu.edu.au  

Closing date: 7 July 2019

Position description: Research Fellow/Fellow

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

Applicants must apply online via the ANU recruitment portal and should upload the following separate documents:

  • A detailed curriculum vitae including a full publication list and the names and contact details of at least three referees (four for level C), preferably including a current or previous supervisor, as well as referees with whom you have not directly worked. If your CV does not include referees you can complete these online when prompted in the application form.
  • A statement addressing the selection criteria.
  • A 1-2 page statement outlining your approach to coursework education and student project supervision.
  • A 1-2 page statement outlining your research objectives for the next 3 years if appointed.

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