University of Sydney
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1 week ago
Fully Funded PhD in Multi-Agent Coordination, Mission Design, and Spacecraft Perception University of Sydney in Australia
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD position with a pre-doctoral salary for up to 4 years.
Deadline
Oct 30, 2026
Country
Australia
University
University of Sydney

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About this position
Dr. Islam is seeking a highly motivated PhD candidate to join a research group at the University of Sydney in Australia. This is a fully funded PhD opportunity with a pre-doctoral salary for up to 4 years, aimed at students interested in space systems and intelligent autonomy.
The project spans three core research directions: multi-agent coordination for safe maneuvering of multi-satellite architectures; mission design for novel space architectures, robotic designs, and exploration strategies for new planets; and spacecraft perception using computer vision with event-based and frame cameras, plus astronomical and remote sensing data. The role is well suited to candidates with interests in Aerospace Engineering, Mechanical Engineering, Mechatronics, Computer Science, Machine Learning, Mathematics, Physics, Robotics, and related quantitative fields.
Eligibility highlights include a completed or near-completion Master’s degree, strong Python programming skills, and ideally experience with a deep learning framework such as PyTorch or JAX. A strong research profile is preferred, including a high-quality Master’s thesis, open-source contributions, or workshop papers. Prior exposure to astrodynamics and spacecraft attitude control is desirable.
To apply, email your CV, transcript, cover letter stating your earliest start date and motivation, and a copy of your thesis or publications to [email protected] by 2026-10-30. Shortlisted candidates will be invited for interview, with commencement expected in Q1/Q2 2027 and a start window noted as March–September 2027.
Funding details
Fully funded PhD position with a pre-doctoral salary for up to 4 years.
What's required
Applicants should have a completed or near-completion Master's degree in Aerospace Engineering, Mechanical Engineering, Mechatronics, Computer Science, Machine Learning, Mathematics, Physics, or a related quantitative field. Strong programming skills in Python and ideally experience with a major deep learning framework such as PyTorch or JAX are expected. An early research track record is preferred, such as a strong Master's thesis, open-source contributions, or workshop papers. Experience in astrodynamics and attitude control of spacecraft is desirable.
How to apply
Email your CV, transcript, cover letter with earliest start date and motivation, and a copy of your thesis or publications to [email protected]. Qualified candidates will be invited for an interview.
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