Research Fellow - Computational Science

Job no: 537901
Work type: Fixed Term
Location: Canberra / ACT
Classification: Academic Level B
Salary Package: $99,809 – $113,165 per annum plus 17% superannuation
Terms: Full time, Fixed term (3 years)

• Exciting opportunity to undertake research at the interface of applied machine learning and high performance computing
• Enable the next generation of computational science through the development of start-of-the-art software solutions
• Engage with outstanding research students from Australia's top university

The Research School of Computer Science (RSCS) is unique in Australia. It includes a creative mix of staff and students that embrace the breadth of computer science profession. It is a diverse and vibrant community dedicated to discovery and to making knowledge matter. It contains world-class academics undertaking high-quality research, training of research students and delivering coursework teaching programs.

Our focus on excellence is more than an aspiration, it is embedded in our performance expectations for Academic staff within the College, through the development of the Academic Performance Standards. These standards are an integral component of our vision to reimagine Engineering and Computer Science research and education, and to continue to propel us on our trajectory of becoming a world-class institution in this space. The CECS Academic Performance Standards provide an overview of key performance indicators they apply to the various academic levels, and support our principles and values of: collegiality, collaborative teamwork, common strategic intent, nurturing early career academics and acting with purpose and professionalism.

Position overview

This position is a fixed term appointment for a period of three (3) years to contribute to computational science objectives and develop collaborations with researchers in the physical sciences.  The Research Fellow will be a key member of a new multi-disciplinary team to research and develop next-generation AI-guided sampling systems, drawing on high performance super-computing simulations as the exemplar. The project aims to develop software to ensure more efficient and effective generation of materials data sets with low (or no) selection bias but has broader applications for self-guiding computational science and research.  The Research Fellow will innovate data science, active learning and reinforcement learning techniques, and be encouraged to develop new and innovative research directions in their specified scientific impact area.

We welcome and develop diversity of backgrounds, experiences and ideas and encourage applications from individuals who may have had non-traditional career paths, who may have taken a career break or who have achieved excellence in careers outside of academia.

This position will commence after February 1st, 2021.

Application information

Applicants must apply online via the ANU recruitment portal here:

https://jobs.anu.edu.au/cw/en/job/537901/research-fellow

Applicants will be asked to 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 (preferably including a current or previous supervisor, and two with no conflict of interest). If your CV does not include referees you can complete these online when prompted in the application form.  Referees will not be contacted without your permission.
• A statement addressing the selection criteria.
• A 1-2 page statement outlining your approach to coursework education and in particular student project supervision.
• A 1-2 page statement outlining your research objectives for the next 3 years if appointed.
• Samples of software released or under development, if a link to a suitable repository is unavailable.

Please note: The successful applicant must have rights to live and work in Australia