Research Fellow in Distributed Machine Learning for Wireless Networks

Location
Melbourne, Australia
Salary
$97,558 – $104,717 p.a. plus 17% super
Posted
01 Jun 2022
End of advertisement period
18 Jul 2022
Ref
0056111
Contract Type
Fixed Term
Hours
Full Time

Location: Parkville
Role type: Full time / Fixed-term for 12 months
Faculty: Faculty of Engineering and Information Technology 
Department/School: School of Electrical, Mechanical and Industrial Engineering
Salary: Level A.6 to A.8 – $97,558 – $104,717 p.a. plus 17% super

Founded in 1853, the University of Melbourne is Australia’s #1 university and is consistently ranked amongst the leading universities in the world. We are proud of our people, our commitment to research and teaching excellence, and our global engagement.

About the School of Electrical, Mechanical and Industrial Engineering

The School of Electrical, Mechanical and Infrastructure Engineering (EMI) undertakes teaching and research across a range of disciplines that are internationally recognised for their contribution to fundamental research. A major focus of the School is to attract and retain outstanding and internationally recognised academic staff. EMI is committed to increasing the number of female engineers and scientists on its staff.

About the Role

You will conduct cutting-edge research within the context of the ARC Linkage Project “RAINBOW - RAdIo Networks Based On distributed machine learning for situation aWareness.” This interdisciplinary, basic research project (TRL 1-2) brings together exciting research topics of security games, wireless communication networks, and distributed and adversarial machine and deep learning. You will use advanced mathematical analysis supported by state-of-the-art simulation-based experiments to obtain novel research results, to be published in relevant Tier-1 conferences and journals.

You will be closely collaborating with other researchers, especially with the other Chief Investigators of the project from the School of Computing and Information Systems (CIS) as well as the industry partner Northrop Grumman Corporation, USA. Additionally, you will have opportunity to collaborate with PhD students working in the projects and may be required to undertake small amounts of teaching and research supervision directly related to your area of research.

Responsibilities include:

  • Independently plan and carry out research on the nominated research project and work towards completion of the aims of the project.
  • Be responsible for generating novel research results based on simulations and mathematical analysis, and to communicate this information to the Chief Investigators and collaborators.
  • Contribute to teaching, training, scientific mentoring and supervision of students;
  • Supervise junior research staff in the appointee’s area of expertise;

About You

You are a passionate researcher with a commitment to quality, as evidenced by publications in leading journals and conferences. You have excellent communication and interpersonal skills that enable you to work effectively with diverse stakeholders and communicate research concepts to technical and non-technical audiences. You have the time management and project management skills necessary to prioritise tasks and meet project milestones.

You will further have:

  • A PhD in Electrical Engineering or Computer Science, or closely related discipline.
  • Research experience in wireless communications and machine/deep learning.
  • Strong mathematical analysis as well as programming skills and familiarity with Python, Scipy and other machine/deep learning libraries.

Benefits of Working with Us

In addition to having the opportunity to grow and be challenged, and to be part of a vibrant campus life, our people enjoy a range of rewarding benefits:

  • Flexible working arrangements and generous personal, parental and cultural leave
  • Competitive remuneration, 17% super, salary packaging and leave loading
  • Free and subsidised health and wellbeing services, and access to fitness and cultural clubs
  • Discounts on a wide range of products and services including Myki cards and Qantas Club
  • Career development opportunities and 25% off graduate courses for staff and their immediate families

To find out more, please visit https://about.unimelb.edu.au/careers/staff-benefits.

Be Yourself

At UoM, we value the unique backgrounds, experiences and contributions that each person brings to our community, and we encourage and celebrate diversity. Indigenous Australians, those identifying as LGBTQIA+, females, people of all ages, with disabilities or culturally diverse backgrounds are encouraged to apply for our roles. Our aim is to create a workforce that reflects the community in which we live.

Join Us!

If you feel this role is right for you, please submit your application including a brief cover letter and your Resume. You are NOT required to respond to Selection Criteria as part of your application.

Should you require any reasonable adjustments with the recruitment process, please contact the Talent Acquisition team at hr-talent@unimelb.edu.au.

Due to the impacts of COVID-19, we are currently prioritising applications with current valid working rights in Australia and candidates who are not affected by travel restrictions. Please see the latest updates to Australia's immigration and border arrangements: https://covid19.homeaffairs.gov.au/

The University of Melbourne is required to comply with applicable health guidance and directions issued from the Victoria Health Minister. The University of Melbourne requires all University of Melbourne employees to be fully vaccinated against COVID-19, unless an exemption order applies. All applicants therefore must meet this requirement when submitting an application.

Position description: 0056111_Research Fellow in Distributed Machine Learning PD.pdf

Applications close: 18 JULY 2022 11:55 PM AUS Eastern Standard Time

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