Employer name: Australian National University
Salary: AUD 71,509 – AUD 90,215 pa plus 17% superannuation
Location (city/country): Canberra/Australia
Closing date: 31 October 2018
The Postdoctoral Fellow will contribute to the ARC Discovery Project grant "Dimension reduction and model selection for statistically challenging data" and will be working closely with the Chief Investigators of the project: Professor Alan Welsh, Dr Francis Hui of the Mathematical Sciences institute, ANU, and Professor Samuel Mueller of the School of Mathematics and Statistics, The University of Sydney. The Postdoctoral Fellow will have the opportunity to spend several weeks each year at The University of Sydney to work with Professor Mueller, to undertake research related to the project, to further enhance research collaboration and build networks. In addition, the postdoctoral fellow will have multiple opportunities to present their findings at domestic and international conferences and workshops.
Applicants are expected to have an outstanding research record in Statistics or a related area, as evidenced by publications in peer-reviewed journals and attendance at workshops and conferences. Preference will be given to candidates who have experience in methodological and theoretical statistics, and good computer skills.
This is a research intensive position; however, an appointee may have an opportunity for teaching.
1. A PhD in Statistics, or must have submitted PhD thesis in Statistics prior to starting employment, with a track record of independent research in the field of Statistical Science as evidenced by publications in peer reviewed journals and conferences.
2. Potential for significant research discovery in Statistics. Research experience in methodological and theoretical statistics together with proven computing skills will be highly regarded.
3. Excellent oral and written English language skills and a demonstrated ability to communicate and interact effectively with a variety of staff and students in an academic environment and to foster respectful and productive working relationships with staff, students and colleagues at all levels.
4. Capacity to contribute to research through written publications and presentations, in particular in statistics.
5. A demonstrated high-level understanding of equal opportunity principles and a commitment to the application of these policies in a University context.