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Research Fellow

Job No.: 601042

Location: Clayton campus

Employment Type: Full-time

Duration: 3-year fixed-term appointment

Remuneration: $97,203 - $115,429 pa Level B (plus 17% 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.

Monash University strongly advocates diversity, equality, fairness and openness. We fully support the gender equity principles of the Athena SWAN Charter and invite you to join us in celebrating women in STEMM.

The Opportunity

The Faculty of Information Technology at Monash is investing significantly in AI and data science by bringing together multidisciplinary teams to develop and understand future technologies and consider the impact of innovation in this area. The faculty partners with industry to roll out ground-breaking AI solutions.

At Monash FIT there is a passionate dedication to research that is both theoretical, and practical and hands-on.  As a result, an opportunity exists for an individual who is talented in both the fields of academic research and software engineering to combine their passions, to support the probabilistic and deep machine learning theme within our broader machine learning team.  Ideally, the successful candidate would do research in probabilistic models, including deep learning, and the development part of the position would flow naturally with the research part, under the direction of academic staff or senior research fellows within the Data Science and AI group.

To be successful for these roles, you will be a goal-oriented individual with a PhD in Computer Science or an equivalent advanced qualification, with a proven track record in refereed research papers, reports or publications.  Your ability to work independently (or with limited supervision) will also be highly regarded, as will your strong technical and/or machine-learning skills. 

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

The Melbourne Area

For six consecutive years, Melbourne has been rated the #1 city worldwide for quality of life (see Economist & Guardian), with excellent education, healthcare, infrastructure, low crime, and exceptional cuisine, cultural activities, and creative design. The regional area is renowned for its dramatic coastline, extensive parks, exotic wildlife, and the Yarra Valley wine region.

This is a unique opportunity to join a leading “Group of 8” University with top-rankings and like-minded, passionate academics. If you feel you have the drive and expertise to contribute to this cutting-edge group, then we encourage you to apply!

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.

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

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

Enquiries

Professor Wray Buntine, Data Science and AI, wray.buntine@monash.edu

Position Description

Download FileResearch Fellow

Closing Date

Wednesday 8 January 2020, 11:55 pm AEDT

#LI-DNI

Supporting a diverse workforce



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