Research Fellow

1 week ago

Canberra, Australia Australian National University Full time

**Classification**:Academic Level B

**Salary package**:$103,841 to $117,736 per annum plus 17% superannuation

**Term**: Full time, Fixed Term (12 months) - possible extension to three years
- Join Computer Vision at ANU Computing, one of the world's leading computer vision schools.
- Conduct high impact, fundamental research on RGB-D and 3D vision and segmentation using weakly/semi-supervised approaches.
- Work partnering with Ford on Vision for Autonomous vehicles.

**College overview**

The Australian National University (ANU) College of Engineering and Computer Science (CECS) is a vibrant and diverse community of more than three thousand students, staff, and visitors. Our College is comprised of three schools: the School of Computing, School of Cybernetics, and School of Engineering, supported by the Professional Services Group. We aim to bring together expertise in social, technical, ecological and scientific systems to build a new approach. In the College, we draw on our disciplinary foundations to find and solve problems of global importance. Our people build on our traditional world-class expertise and take it in creative, unconventional directions. Through the Reimagine investment, we have the privilege and the responsibility to build a new legacy for the University, the country, and even the world. We will deliver on our mission by building a strong community, providing transformative educational experiences, conducting high-impact research, seeking meaningful engagement, and becoming a resilient organisation post COVID-19. Join us in shaping a new intellectual agenda to reimagine engineering, computing, and the use of technology in the world.

The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades of computer science methodologies with modern data and computational science. Our mission is motivated by the need to design, drive and sustain strategic activities via five broad focus areas: Computing Foundations, Computational Science, Intelligent Systems, Data Science and Analytics, and the Software Innovation Institute. Be part of an innovative and forward-looking intellectual agenda, built on a diverse, inclusive culture.

**Position overview**

This position is a fixed term for a period of 1 year with possible extension funding contingent appointment to contribute to research in weakly/semi supervised techniques for RGB-D and Point Cloud segmentation, in partnership with Ford. Applications are invited from researchers tho undertake high impact collaborative research, particularly in 3D vision, segmentation, and weakly/semi supervised approaches.

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.

**Application information**
- A max 1-2 page statement addressing the selection criteria.
- (Optional) a statement addressing past and/or potential contributions to diversity through research, teaching, and/or service.
- (Optional for applicants) achievement relative to opportunity statement where appropriate

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

**Please note: The successful applicant must have rights to live and work in this country and 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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