Research Fellow in Reinforcement Learning

Location
Melbourne, Australia
Salary
$77,171 – $104,717 p.a. plus 17% super, minimum salary for PhD graduate - $97,558
Posted
06 Jul 2022
End of advertisement period
02 Aug 2022
Ref
0055414
Contract Type
Fixed Term
Hours
Full Time

Location: Parkville
Role type: Full-time, fixed term for 12 months (possibility of extension)
Faculty: Faculty of Engineering and Information Technology
Department/School: Department of Electrical and Electronic Engineering
Salary: Level A – $77,171 – $104,717 p.a. plus 17% super, minimum salary for PhD graduate - $97,558

  • Explore, develop, analyse, and demonstrate various approaches in safe reinforcement learning
  • Ideal role for candidates with expertise in reinforcement learning, optimal control, optimization theory, or system identification
  • Opportunity to grow you career and travel internationally to attend conferences and collaborate with research groups

The University of Melbourne would like to acknowledge and pay respect to the Traditional Owners of the lands upon which our campuses are situated, the Wurundjeri and Boon Wurrung peoples, the Yorta Yorta Nation, the Dja Dja Wuurang people. We acknowledge that the land on which we meet and learn was the place of age-old ceremonies, of celebration, initiation and renewal, and that the local Aboriginal peoples have had and continue to have a unique role in the life of these lands.

The Faculty of Engineering and Information Technology (FEIT) is strongly committed to supporting diversity and flexibility in the workplace. Improving the representation of women is necessary in our goal to innovate and to strengthen FEIT’s reputation as a best-in-class centre of research.

Applications for part-time or other flexible working arrangements will be welcomed and will be fully considered subject to meeting the inherent requirements of the position.

School of Electrical, Mechanical and Infrastructure Engineering (EMI) recognises that engineered systems of present and future significance increasingly have connections to all three.

We are the oldest engineering school in Australia – initially founded in 1861 – and have evolved into a vibrant community of internationally recognised researchers passionate about addressing major challenges of today and into the future.

About the role:

The Research Fellow will work on reinforcement learning, or other data-driven control methodologies, with a view to ensure constraint satisfaction during both the learning and deployment phases to avoid unsafe behaviour.

The use of learned models and controllers is becoming prevalent. Online learning can create adaptable algorithms for control in unknown or time-varying environments or for plug-and-play interaction with other systems. However, criticality of applications, such as autonomous driving and flight, demands constraint satisfaction during the training to still guarantee safe operation while adapting the controllers online. In this position, you will explore, develop, analyse, and demonstrate various approaches in safe reinforcement learning for linear and nonlinear dynamic models. Extensions to multi-agent planning and control will be highly desirable.

There is funding available for attending international conferences and visiting an internationally recognized research group for collaboration on the topic of this position. The research group has longstanding collaboration links with researchers from the University of California Irvine, University of Illinois Urbana-Champaign, Princeton University, Australian National University, and KTH Royal Institute of Technology.

Responsibilities include:

  • Providing expertise in design, analysis, and demonstration of reinforcement learning and data-driven control with constraint satisfaction for safety.
  • Publication of high-quality research papers on the topic of reinforcement learning and data-driven control in peer-reviewed top journals and conferences in computer science and control engineering.
  • Providing project representation to various internal or external stakeholders.
  • Attending and participating in relevant meetings, seminars, and conferences.
  • Contributing to training, mentoring, and supervision of students.

About You

You are a confident communicator with well-developed interpersonal and negotiation skills with the ability to build and maintain relationships with internal and external stakeholders within a diverse work environment. You are organised, detail oriented with a strong work ethic, commitment to continuous improvement, openness to new ideas and creative approaches to problem solving within established timelines.

Ideally, you will further have:

  • A PhD in Engineering, Computer Science, or Applied Mathematics.
  • A solid understanding of the theory of at least of one of the topics of reinforcement learning, optimal control, optimization theory, or system identification.
  • An excellent track record of quality research as evidenced by publications in the top peer-reviewed journals and conferences of systems and control, signal processing, computer science, or applied mathematics.

For specific responsibilities of this role please refer to the attached Position Description.

You will be supported to pursue achievement in all pillars of an academic career:

  • Research & Research Training
  • Contribution to Teaching and Learning
  • Engagement
  • Service and Leadership

About the University

The University of Melbourne 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.

Benefits of Working with U

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, 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, visit https://about.unimelb.edu.au/careers/staff-benefits.

Be Yourself

We value the unique backgrounds, experiences and contributions that each person brings to our community and encourage and celebrate diversity.  First Nations people, those identifying as LGBTQIA+, females, people of all ages, with disabilities and culturally and linguistically diverse people are encouraged to apply. 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 apply with your CV and cover letter outlining your interest and experience. Please note that you are not required to provide responses against the selection criteria in the Position Description.

We are dedicated to ensuring barrier free and inclusive practices to recruit the most talented candidates. If you require any reasonable adjustments with the recruitment process, please contact us at hr-talent@unimelb.edu.au.

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

While we review your application, get to know us by visiting http://www.eng.unimelb.edu.au/about/join-feit

Applications close: TUESDAY 02 AUGUST 2022 11:55 PM AUS Eastern Standard Time

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