Professor in Statistical Data Science
Queensland University of Technology
School of Mathematical ScienceClosing date: 1st October 2017
Remuneration and Benefits
The classification for this position is Academic Level E (LEV E) which has an annual remuneration range starting at $AUD206,729 pa. Which is inclusive of an annual salary of $ AUD174,688 pa, 17% superannuation and 17.5% recreation leave loading.
About the Position
The School of Mathematical Sciences at QUT has an exciting position for a Professor (Level E) in Statistical Data Science who is able to provide strategic leadership in both research and learning within the Discipline of Statistics and Operations Research. More widely, the Professor will strongly contribute to QUT’s research priority in Data Science, which aims to improve the knowledge mined from data by combining mathematics, machine learning and statistical methods with information technologies.
The Professor will help to lead, maintain and expand our research expertise in developing new methodologies, knowledge and insights from the large amounts of data collected by government and industry. They will have expert knowledge and practical experience in fundamental data science problems, including classification, inference, regression, clustering, dimension reduction and feature selection, for example. Big data analytics and visualisation, machine learning, deep learning, large-scale data mining and/or computational statistics are all of potential interest.
The Professor will have a strong record of high quality publications (among leaders in the field) and in the generation of competitive and commercial research income. They will also have a strong record of mentoring early and mid-career academic staff and the supervision of higher degree research students and be committed to the development and delivery of high quality learning experiences for statistics, operations research, engineering, science and health science students who want to combine their studies in statistics with real-world applications and computational simulations.
Necessary to the success of the position is the fostering of partnerships with both internal and external groups in developing research programs. The Professor will link with the ARC Centre of Excellence in Mathematical and Statistical Frontiers (ACEMS), led at QUT, by Professor Kerrie Mengersen as well as other data science practitioners within the university including academics in the Data Science Discipline in the School of Electrical Engineering and Computer Science and the ARC Centre of Excellence in Robotic Vision led by Professor Peter Corke which is hosted at QUT.
This position reports to the Head of School of Mathematical Sciences for supervision, workload management and for Performance Planning and Review (PPR).
For more information and to apply, click here.
**Mention you saw it on the AustMS website**