Research Fellow in Econometrics and Business Statistics
3 days left
- Full Time
Faculty / Portfolio: Faculty of Business and Economics
Department of Econometric and Business Statistics
Location: Clayton campus
Employment Type: Full-time
Duration: Two year fixed-term appointment
Remuneration: $92,074 - $109,339 pa Level B
(plus 9.5% employer superannuation)
- Achieve at one of the top 100 universities in the world
- Where international collaboration is pursued
- Plenty of reasons to be inspired
If you're after a rewarding career, Monash University can help make it happen. With leading academics and world-class resources, combined with a ranking in the top 100 universities worldwide, we offer all you need to build a brighter future.
The Department of Econometrics and Business Statistics (EBS) is recognised worldwide for the quality of its research and teaching and has been designated by Monash as an area of outstanding strength, "demonstrably pre-eminent relative to other Australian universities and competitive with the strongest international equivalents". In the Excellence in Research for Australia assessment conducted by the Australian Research Council in 2015, Monash University received a rank of 5, which is the highest possible rank, in Econometrics.
EBS is seeking a highly motivated Research Fellow to undertake and contribute to research, under the auspices of ARC Discovery Grant DP170100729: "The Validation of Approximate Bayesian Computation: Theory and Practice". Prof Gael Martin and Dr David Frazier are the Chief Investigators on the grant, and international researchers Prof Christian Robert and Prof Eric Renault are Partner Investigators.
The Research Fellow will be involved in research projects associated with the grant, under the direction of Prof Gael Martin and Dr David Frazier.
To be successful you will have a relevant doctoral qualification in econometrics or statistics (or equivalent relevant research experience) with specific expertise in one or more of the following areas: Bayesian statistical methods, including modern computational techniques; frequentist simulation-based inference; statistical theory; asymptotic analysis.
You will also possess sound interpersonal skills, along with excellent written and oral communication abilities.
If you believe you fit this profile, we look forward to receiving your application.
This role is a full-time position; however, flexible working arrangements may be negotiated.
Your application must address the selection criteria. Please refer to "How to apply for Monash jobs"
Professor Gael Martin, Gael.Martin@monash.edu
Friday 28 April 2017, 11:55pm AEST
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