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Research Fellow

Job No.: 588550

Location: Clayton campus

Employment Type: Full-time

Duration: 2 year fixed-term appointment

Remuneration: $68,040 - $92,343 pa Level A (plus 9.5% employer superannuation)

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

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. You’ll have access to quality research, infrastructure and learning facilities, opportunities to collaborate internationally, as well as the grants you’ll need to publish your work. 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.

The Opportunity

The Faculty of Information Technology aims to lead global IT research and education. The Data Science and AI group is seeking a go-getter Research Fellow to work at the interface of computer science, machine learning and medical research. You will be involved in potentially ground-breaking research developing and implementing algorithms and software to predict the risk of a woman developing breast cancer using digital, pre-diagnosis mammographic images.

As the successful candidate you will combine an enthusiasm for data science research with a doctoral qualification in Computer Science, Statistics or a closely related field. Experience with image processing and/or deep learning is desirable, but not necessary.

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

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

Your application must address the selection criteria. Please refer to "How to apply for Monash Jobs".

Enquiries

Dr Daniel Schmidt, Senior Lecturer, Data Science, +61 3 9905 9985

Position Description

Download File Research Fellow

Closing Date

Thursday 4 April 2019, 11.55pm AEDT

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