Monash University: Research Fellows, Statistical Learning, Time Series, Relational/Structural Learning [Melbourne, Australia]

At: Monash University
Location: Melbourne, Australia
Web: www.monash.edu
Position: Research Fellows: Statistical Learning, Time Series, Relational/Structural Learning
 
Apply here.

 
Employment Type: Full-time
Duration: 3 year fixed-term appointment
Remuneration: $97,203 - $115,429 pa Level B (plus 9.5% employer superannuation)

• Be inspired, every day
• Take your career in exciting and rewarding directions at one of the world’s top 80 universities

Everyone needs a platform to launch a satisfying career. At Monash, we give you the space and support to take your career in all kinds of exciting new directions with access to quality research, infrastructure and learning facilities. We’re a university full of energetic and enthusiastic minds, driven to challenge what’s expected, expand what we know, and learn from other inspiring, empowering thinkers. Innovative, supportive, successful and with great breadth and depth of talent, Monash Information Technology is a leader in research and education. We provide an ideal environment in which to excel and are located in Melbourne, one of the world’s most liveable cities.

The Opportunity

An exciting opportunity has opened up within our world-class Faculty of Information Technology for three Research Fellows to conduct research in collaboration with world class academics; Professor Wray Buntine, Dr Reza Haffari and Professor Geoff Webb, as part of our leading-edge research. The three openings relate to the following areas:

• Statistical learning: work with Professor Wray Buntine, Professor Dinh Phung, Dr Daniel Schmidt and Dr David Albrecht on Bayesian approaches to deep neural networks. This group has shared interests in developing supervised, semi-supervised, multi-label and unsupervised deep neural networks in the context of multi-task learning and learning with limited supervision.
• Time series: work with Professor Geoff Webb, Dr Christoph Bergmeir, Dr Francois Petitjean, Dr Mahsa Salehi and Dr Levin Kuhlmann on research into time-series classification and regression. This will build collaboration between this group who have been working in different but related areas of time series research.
• Innovative Solutions: work with Dr Reza Haffari, Dr Teresa Wang, Dr Lan Du, Dr Shirui Pan and Dr Xiaojun Chang on Bayesian approaches to relational and structural learning. Relational and structural learning studies machine learning methods for the analysis of complex and large scale relational or graph structured data. This will construct collaboration between this group who have been working in different but related areas of relational learning research.

To be successful in securing these exciting opportunities you will have a doctoral qualification within Computer Science, or equivalent qualifications or research experience; demonstrated knowledge within the respective areas; and a burning desire to work alongside the premier academics in the field producing world-class research.

Please indicate your preferred research area within your cover letter.

This role is a full-time position; however, flexible working arrangements may be negotiated.

The faculty is strongly committed to improving the diversity of our staff and students, and promoting a culture of equity, fairness, respect and openness. We fully support the gender equity principles of the Athena SWAN Charter.

At Monash University, we are committed to being a Child Safe organisation. Some positions at the University may require the incumbent to hold a valid Working with Children Check.

For instructions on how to apply, please refer to “How to apply for Monash Jobs”.

Enquiries

Professor Wray Buntine, Machine Learning Group Lead, wray.buntine@monash.edu
 
Position Description

• Research Fellow - Statistical Learning
• Research Fellow - Time Series
• Research Fellow - Innovative Solutions

Closing Date

Wednesday 3 July 2019, 11:55pm AEST