Publisher
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Rutgers University

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Fully Funded PhD Positions in Space Systems, Autonomy, and AI at Rutgers University Rutgers University in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded research assistant positions are available for selected PhD students.

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Country

United States

University

Rutgers University

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Aerospace Engineering
Mathematics
Artificial Intelligence
Astrodynamics
Autonomy
Optimisation
Technical Engineering
Robotics
Physics
ML

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About this position

Funded PhD Research Assistant positions are available in the X-Bai Research Group at Rutgers University for students interested in space systems, autonomy, and AI.

The group develops intelligent, autonomous, and reliable capabilities for future space systems, with research interests spanning astrodynamics, optimization, robotics, machine learning, mathematics, physics, and broader engineering topics.

These positions begin in Spring, Summer, or Fall 2027 and are described as fully funded for selected students.

Applicants should be highly qualified and strongly motivated, with strong fundamentals and research maturity. The post emphasizes a willingness to keep learning new theories, computational methods, experimental techniques, and modern research tools.

To apply, interested students should email Professor Xiaoli Bai directly at [email protected] with a CV, academic transcripts, and a brief statement covering prior research experience, technical contributions, strongest relevant background, research interests in the X-Bai Research Group, and fit with the group.

Applicants are also asked to review the X-Bai Research Group website and current research directions before contacting the professor.

Funding details

Fully funded research assistant positions are available for selected PhD students.

What's required

Applicants should be highly qualified and strongly motivated PhD students with strong fundamentals and research maturity. Preferred backgrounds include relevant technical experience in mathematics, physics, engineering, astrodynamics, optimization, robotics, machine learning, and space science. Applicants should be willing to continually learn new theories, computational methods, experimental techniques, and modern research tools. A CV, academic transcripts, and a brief statement of prior research experience, technical contributions, strongest relevant technical background, research interests in the group, and fit are requested.

How to apply

Email Professor Xiaoli Bai directly at [email protected] with your CV, academic transcripts, and a brief statement of research experience, technical contributions, relevant background, and fit. Review the X-Bai Research Group website and current research directions before contacting.

More information can be found here

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