Research Fellow in Information Theory and Machine Learning

Location: Parkville
Role type: Full time; Fixed-term for 2 years
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

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 Wurrung 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.

About - Faculty of Engineering and Information Technology

https://eng.unimelb.edu.au/

The Faculty of Engineering and Information Technology (FEIT) has been the leading Australian provider of engineering and IT education and research for over 150 years. We are a multidisciplinary School organised into three key areas; Computing and Information Systems (CIS), Chemical and Biomedical Engineering (CBE) and Electrical, Mechanical and Infrastructure Engineering (EMI). FEIT continues to attract top staff and students with a global reputation and has a commitment to knowledge for the betterment of society.

FEIT has never been better positioned as a global leader, anchored in the dynamic Asia Pacific region, creating and curating knowledge to address some of the world’s biggest challenges. Through our students and our relationships with communities, we can not only respond to society’s needs but anticipate and create engineering and IT solutions for the future.

About - Department of Electrical and Electronic Engineering
https://electrical.eng.unimelb.edu.au/

The Department of Electrical and Electronic Engineering is a vibrant community of internationally recognised researchers focused on addressing major challenges in Power Systems; Computation and Communication Networks; Electronic & Photonic Devices and Materials; and Systems Engineering. We have long-standing, strong partnerships with industry and government that support our researchers in conducting high impact research. The Department offers both PhD and Masters level research degrees and the postgraduate coursework Masters of Electrical Engineering. The Department also contributes to the Electrical Engineering Systems major in the Bachelor of Science. 

About the Role

The Research Fellow will work on topics in information theory and machine learning, with a focus on using information-theoretic methods and tools to study statistical machine learning problems. Recent development of machine learning theory has witnessed renewed interests in using information-theoretic tools to understand learning algorithms. Examples include evaluating the performance of algorithms (generalization error or excess risk) with information-theoretic measures and designing novel learning algorithms based on these measures. The Research Fellow will explore, analyse, develop, and demonstrate various approaches in applying information-theoretic methods to investigate statistical learning problems. While the research program is guided by a set of research questions, there will be considerable scope for the Research Fellow to develop their own ideas within a broader research agenda.

You will conduct independent research, leading to the preparation and publication of research outcomes in conferences and journals. You will be located in the Department of Electrical and Electronic Engineering in the Faculty of Engineering and Information Technology (FEIT) and will be expected to be an active member of the Department, collaborating with other researchers. You may undertake small amounts of teaching and research supervision directly related to your area of research, as required.

Responsibilities include:

• Providing expertise in design, analysis, and demonstration of learning algorithms with information-theoretic methods.
• Publication of high-quality research papers on the topic of information theory and machine learning.
• Actively participating in the communication and dissemination of research
• Effectively liaising with external networks to foster collaborative partnerships
• Contributing to teaching, training, scientific mentoring and supervision of students

For further information about this role, please contact Dr Jingge Zhu on jingge.zhu@unimelb.edu.au 

About You

To be successful in this role you will have the capability for innovative research, as evidenced by scholarly publication. You will have excellent written and verbal communication skills, demonstrated by presentation of research results at conferences, internal forums and through manuscript submissions. You will also have experience in using initiative, working with minimal supervision and ability to prioritise tasks to achieve project objectives within timelines.

You will also have:

• A PhD in electrical engineering (information theory, machine learning, communication, or signal processing) or neighbouring topics including, but not limited to, computer science, applied mathematics.
• A solid understanding of the theory of at least of one of the topics of information theory, statistical learning theory, communication systems.
• An excellent track record of quality research as evidenced by research publications in the top journals and conferences of the systems and control, computer science, or applied mathematics.
• Ability to perform independent research and a commitment to interdisciplinary research
• Demonstrated capacity to communicate research concepts to technical and non-technical audiences
• Excellent interpersonal skills, including an ability to interact with internal and external stakeholders (academic, administrative and support staff) in a courteous and effective manner

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 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, 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.

Position description: 0058903_Research Fellow in Information Theory and Machine Learning_PD.pdf

Applications close: 5 April 2023 11:55 PM AUS Eastern Daylight Time