Research Fellow
4 weeks ago
**Classification**:ANU Academic Level B
**Salary package**:$107,475- $121,857 plus 17% superannuation
**Term**: Full time, Fixed Term (1 year)
ANU is looking for a Research Fellow to join a 3D fitting optimisation and machine learning project with real-life impact.
- The aim is to design, implement, and evaluate data-driven solutions for specified key decision and optimisation problems
- Flexible working arrangements
**About Us**
The _ANU by 2025_ Strategic Plan calls for the University to serve society through transformational research and education. As one of the great universities of the world, ANU is driven by a culture of excellence in everything we do. Our lived experience is increasingly one of large-scale systems of people, whose actions and interactions are influenced by our digital, physical and biological environment. The ANU College of Engineering, Computing and Cybernetics (CECC) hosts three of the key disciplines necessary to help us design, build, regulate and secure the future.
CECC brings together expertise in social, technical, computational, ecological and scientific systems to build a new approach to systems design and build new national capabilities in data-driven policy and business development. The work we do in the College directly supports one of the four pillars of _ANU by 2025_: to strengthen our national mission and meet our unique responsibilities as Australia’s national university. 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.
We welcome and openly acknowledge differences in expertise, research / education / professional focus, experience and perspective. CECC is a vibrant and diverse community of more than three thousand students, staff, and visitors. Our College comprises three schools: the School of Computing, School of Cybernetics, and School of Engineering, supported by the Professional Services Group.
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.About the opportunity
**Position description and selection criteria**:
This position is a fixed term for a period of 1 year appointment to:
- Support the development of partnerships with industry and engage with the wider research community to embed progressive engineering and computing research and education capabilities.
Applications are particularly invited from researchers who undertake high impact collaborative and cross-disciplinary research, and whose expertise contributes to Data Science and Analytics.
**Selection criteria**
- A PhD or equivalent in the field of Computer Science, or a related area as relevant to the research to be undertaken, with a competitive track record of research and impact as evidenced by appropriate outputs and measures of esteem in industry, government or academic environments.
- Demonstrated experience developing, applying, analysing, and evaluating the effectiveness of data-driven decision and optimisation methods in the context of applied research, explaining and justifying design decisions to project stakeholders, and implementing solutions as part of an integrated system in collaboration with a wider project team. Knowledge of and experience with a wide range of machine learning methods (ranging from decision trees, nearest neighbours, and support vector machines to more recent deep learning architectures) optimisation methods, and computational geometry are all desirable.
- Evidence of effective collaboration, team-based projects and interdisciplinary activities and interests. In particular, evidence of ability and experience in effectively establishing on-going support for industry-academia engagement, collaboration and partnerships.
- An ability to contribute to impact and engagement activities involving government, industry, the wider research community and the general public, including involvement in collaborations and partnerships with a range of internal and external stakeholders.
- Excellent communication skills with the ability to inspire a wide range of audiences, including in cross-disciplinary areas and to foster respectful and productive working relationships with staff, students and colleagues
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