Macquarie University
1 week ago
Research Fellow in Machine Learning for LEO Satellite Communications Macquarie University in Australia
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time fixed-term research fellow appointment for 2 years with a possibility of renewal subject to funding. Salary package is AUD 112,550–120,621 per annum (Level A6-A8), plus 17% employer superannuation and annual leave loading. Visa sponsorship is available for the successful candidate, subject to eligibility.
Deadline
Oct 30, 2026
Country
Australia
University
Macquarie University

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About this position
Macquarie University is advertising a Research Fellow position in machine learning for low-Earth orbit (LEO) satellite communications, based at the Wallumattagal Campus in North Ryde, Sydney, Australia.
The project, Brain-in-Space: A Machine Learning Framework for Self-Organizing Low-Earth Orbit Satellite Networks, is funded by the Global Science and Technology Diplomacy Fund. The successful candidate will investigate how LEO satellites can act as intelligent agents that learn, coordinate, and adapt to changing orbital and traffic conditions. The work combines machine learning, mathematical modelling, algorithm design, and development of an open-source simulation and benchmarking platform.
You will work closely with Dr Hazer Inaltekin at Macquarie University and international collaborators including Associate Professor Wonjae Shin (Korea University), Professor Jungwoo Lee (Seoul National University), and Professor Vincent Poor (Princeton University). The role includes opportunities to publish, contribute to postgraduate supervision, and build an international research profile.
Eligibility highlights: a PhD in electrical and electronic engineering, computer science, applied mathematics, or a related discipline; strong publication record; strong mathematical and algorithmic skills; experience applying machine learning to research problems; programming skills in Python and/or MATLAB; and strong communication and teamwork abilities. Desirable experience includes information theory, communication theory, satellite communications/networking, sequential decision-making, multi-agent coordination, and simulation software development.
Funding and conditions: full-time fixed-term appointment for 2 years, with possible renewal subject to funding. Salary package is AUD 112,550–120,621 per annum plus 17% superannuation and annual leave loading. Visa sponsorship is available for eligible international applicants.
Application deadline: Friday 30 October 2026 at 11:59 pm AEST. Applicants should submit a resume with publication list, a cover letter addressing the selection criteria (max 2 pages), and referees.
Funding details
Full-time fixed-term research fellow appointment for 2 years with a possibility of renewal subject to funding. Salary package is AUD 112,550–120,621 per annum (Level A6-A8), plus 17% employer superannuation and annual leave loading. Visa sponsorship is available for the successful candidate, subject to eligibility.
What's required
A PhD in electrical and electronic engineering, computer science, applied mathematics, or a related discipline is essential. Applicants should have a strong publication record appropriate to career stage, strong mathematical and algorithmic ability, demonstrated experience applying machine learning to research problems, strong programming skills in Python and/or MATLAB, excellent communication skills, the ability to plan and manage research independently, and a commitment to collaborative teamwork. Desirable experience includes information theory, communication theory, satellite communications or networking (especially LEO systems), sequential decision-making or multi-agent coordination, simulation software development, and interest in supervising postgraduate students.
How to apply
Submit an up-to-date resume including publication list, a cover letter addressing the selection criteria (max 2 pages), and up-to-date referees. For role-specific enquiries, contact Dr Hazer Inaltekin at [email protected]. Apply before the closing date through the SEEK/Macquarie application process.
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