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Monash University: Research Fellow in Time Series Classification

Looking for an outstanding Research Fellow to work with Prof Geoff Webb and Dr Francois Petitjean at Monash Data Science. 18-month appointment - attractive remuneration.

Monash University At: Monash University
Location: Melbourne, Australia
Web: www.monash.edu

Duration: 18 month fixed-term appointment
Remuneration: $92,074 - $109,339 pa Level B, (plus 9.5% employer superannuation)
  • Achieve excellence at a world top 100 university
  • Join an internationally-recognised faculty
  • Pioneer research projects funded by US Air Force
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 Opportunity
The Faculty of Information Technology has a strong focus on multidisciplinary, multi-campus and multinational research. As a result, we have an outstanding global reach which far exceeds any other institution in Australia. We are currently seeking a Research Fellow to support our vision to lead and propel global IT research and education.

In this role, you will conduct cutting-edge research into algorithms for Time Series Classification and Machine Learning from Data Streams, for projects funded by the Australian Research Council and by the US Air Force Research Laboratories.

The successful candidate will have an outstanding research track record in a related field of research. You will be a goal-oriented individual with a PhD in Computer Science or a related qualification.

Your ability to work independently (or with limited supervision) will also be highly regarded, as will your strong written and verbal communications skills.

If you are enthusiastic at the prospect of embarking on a ground-breaking challenge, we strongly encourage you to apply!

This role is a fixed-term position for 18 months with full-time hours; however, flexible working arrangements may be negotiated.

Apply online.