Research Associate in Manufacturing Engineering

Canberra, Australia
Tuesday, 14 September 2021
End of advertisement period
Tuesday, 12 October 2021
Contract Type
Fixed Term
Full Time

Work type: Full-time
Location: Canberra, ACT
Categories: Associate Lecturer

UNSW Canberra is a campus of the University of New South Wales located at the Australian Defence Force Academy in Canberra. UNSW Canberra endeavours to offer staff a rewarding experience and offers many opportunities and attractive benefits, including:

  •      One of Australia’s leading research and teaching universities
  •      Strong commitment to staff development and learning
  •      Strong commitment to work life and family balance
  •      Generous superannuation opportunities

At UNSW, we pride ourselves on being a workplace where the best people come to do their best work.

The School of Engineering and Information Technology (SEIT) offers a flexible, friendly working environment that is well-resourced and delivers research-informed education as part of its accredited, globally recognised engineering and computing degrees to its undergraduate students. The School offers programs in electrical, mechanical, aeronautical, and civil engineering as well as in aviation, information technology and cyber security to graduates and professionals who will be Australia’s future technology decision makers.

This research position will work closely with the industry partner to apply machine learning approaches to monitor for spot weld quality. The successful applicant will undertake model development, validation, and assist with industrial in-process verification of the models.

About the Role:

Role:                Research Associate in Advanced Manufacturing
Salary:             Academic Level A $78,890 - $105, 185 plus 17% Superannuation

Term:               Full time, Fixed Term appointment up to 2 years

 About the Successful Applicants

To be successful in this role you will:

  • Hold a Ph.D. degree or equivalent in Engineering, Applied Mathematics, Machining Learning or related discipline;
  • Experience of working with large complex data sets in the context of applied research.
  • A demonstrated ability to apply machine learning techniques for model development of manufacturing systems or other similar physical systems;
  • A record of papers in high quality journals and/or conferences of high ranking in the field;
  • Experience working with industrial partners will be highly desirable;
  • Demonstrated ability to work as a member of a multi-disciplinary distributed team showing initiative and taking direction as appropriate to the situation.

In your application, please upload a 2-page pitch addressing the Skills and Experience outlined in the Position Description.

In order to view the Position Description – please ensure that you allow pop-ups for Jobs@UNSW Portal.

The successful candidate will be required to undertake pre-employment checks prior to commencement in this role. The checks that will be undertaken are listed in the Position Description. You will not be required to provide any further documentation or information regarding the checks until directly requested by UNSW.

The position is located in Canberra, ACT. The successful candidate will be required to work from the UNSW Canberra campus. To be successful you will hold Australian Working Rights or Australian Citizenship. Visa sponsorship is not available for this appointment.

For further information about UNSW Canberra, please visit our website: UNSW Canberra

Matthew Doolan, Associate Professor
P: +61 2 5114 5176

Applications Close: 12 October 2021 11:30PM

Find out more about working at UNSW Canberra

At UNSW Canberra, we celebrate diversity and understand the benefits that inclusion brings to the university. We aim to ensure that our culture, policies, and processes are truly inclusive. We are committed to developing and maintaining a workplace where everyone is valued and respected for who they are and supported in achieving their professional goals. We welcome applications from Aboriginal and Torres Strait Islander people, Women at all levels, Culturally and Linguistically Diverse People, People with Disability, LGBTIQ+ People, people with family and caring responsibilities and people at all stages of their careers. We encourage everyone who meets the selection criteria and shares our commitment to inclusion to apply.

       Any questions about the application process - please email