The X-Bai Research Group at Rutgers University is inviting highly qualified and strongly motivated students to apply for fully funded PhD research assistant positions beginning in Spring, Summer or Fall 2027.
The opportunity is aimed at aspiring researchers interested in space systems, autonomy, artificial intelligence, robotics, machine learning and related advanced engineering fields.
Selected PhD students will receive fully funded research assistant positions while contributing to research focused on developing intelligent, autonomous and reliable capabilities for future space systems. The group offers an opportunity for doctoral researchers to work at the intersection of fundamental scientific research and advanced technological applications.
Students joining the X-Bai Research Group will have opportunities to work with computational modeling, real-world space data, machine learning, robotic experiments and hardware-in-the-loop testbeds.
Fully Funded PhD Research Opportunity at Rutgers University
The X-Bai Research Group is seeking students with strong technical preparation, meaningful prior research experience and a clear connection between their academic background and the group’s current research directions.
The available positions are particularly suitable for students seeking a PhD in areas connected to aerospace engineering, mechanical engineering, electrical engineering, applied mathematics, robotics, computer science, space science, automation and control, as well as closely related disciplines.
Admission to the research group is selective. Prospective applicants are expected to demonstrate strong research capability and clearly explain how their previous training, technical experience and research interests align with the group’s work.
Applicants are therefore encouraged to carefully study the X-Bai Research Group’s research areas before submitting an inquiry.
Research Areas in Space Systems and Autonomy
The group conducts research across several important areas shaping the future of autonomous and intelligent space systems.
One major research area is Astrodynamics and Space Situational Awareness. Research in this area includes orbit determination and prediction, uncertainty quantification, space-object characterization and physics-informed modeling. These topics are important for understanding, predicting and managing the movement and behaviour of objects in space.
Another focus area is Space Robotics and Proximity Operations. Students may conduct research involving autonomous proximity operations, vision-based navigation and pose and motion estimation for unknown space objects. Additional areas include space-manipulator trajectory planning and control, as well as hardware-in-the-loop experimentation.
The research group also works on Thermospheric Density and Space Weather Prediction. This area uses physics-informed machine learning for thermospheric density modeling and forecasting, satellite drag modeling and applications related to orbit prediction and conjunction assessment.
A further major research direction is Physics-Informed and Uncertainty-Aware Machine Learning. This research integrates physics, data and machine learning to support prediction, estimation, planning and decision-making in complex space systems.
Opportunities for Advanced Research and Practical Applications
Students selected for the fully funded PhD research assistant positions will have opportunities to contribute to both fundamental research and advanced applications.
The research environment brings together theoretical and computational approaches with experimental work. Depending on their research projects, PhD students may work with mathematical and computational models, real-world data from space-related applications, machine learning techniques and robotic experimentation.
The use of hardware-in-the-loop testbeds may also provide researchers with opportunities to evaluate and develop advanced systems in an experimental environment.
This combination of theory, data, artificial intelligence and robotics makes the opportunity particularly relevant for students interested in conducting interdisciplinary research at the frontier of space technology.
Who Should Apply?
The X-Bai Research Group is particularly interested in applicants with strong technical foundations and substantial depth in at least one area directly relevant to the group’s research.
Applicants are encouraged to have a strong foundation in mathematics, physics and engineering fundamentals. Competitive candidates should also demonstrate substantial preparation in one or more technical areas.
Relevant areas include:
- Astrodynamics
- Dynamical systems and control
- Estimation
- Optimization
- Robotics
- Machine learning
- Space science
- Advanced control
- Statistics
- Numerical methods
- Scientific computing
- Computer vision
Applicants are not expected to possess expertise in every listed area. However, they should demonstrate meaningful technical depth in at least one field that strongly connects with the group’s current research.
Skills and Qualifications
Competitive applicants should demonstrate strong analytical, mathematical and computational problem-solving abilities.
Solid programming experience is also important, particularly in Python and/or MATLAB. Previous research experience should demonstrate an applicant’s ability to formulate research problems, conduct technical analysis, interpret findings and contribute independently to a research project.
The group is also seeking students with strong motivation to conduct rigorous and high-quality research and successfully complete a PhD programme.
Intellectual curiosity, independence, persistence and the ability to learn unfamiliar concepts and methods quickly are also highly valued.
Knowledge of machine learning, robotics, computer vision, optimization, estimation, numerical methods or related advanced topics may provide an advantage where these skills are relevant to the applicant’s intended research area.
Strong Research Fit Is Essential
Prospective applicants should understand that these PhD research assistant positions are selective.
The X-Bai Research Group particularly values students who combine strong academic and technical fundamentals with research maturity. Successful applicants should be prepared to continually learn new theories, computational methods, experimental techniques and modern research tools.
A clear research fit is especially important. Generic inquiries that do not explain the connection between an applicant’s background and the group’s research directions are unlikely to receive consideration.
Applicants should therefore tailor their application materials and communication carefully, identifying the specific research areas that interest them and explaining why their previous preparation makes them a suitable candidate.
How to Apply
Interested students should contact Professor Xiaoli Bai directly at the email address provided in the official call: xiaoli.bai at rutgers.edu.
Applicants should include the following materials:
- A current CV.
- Academic transcripts.
- A brief statement describing previous research experience.
- Details of specific technical contributions made during previous research.
- Information about the applicant’s strongest relevant technical background.
- The research areas within the X-Bai Research Group that are of greatest interest.
- A clear explanation of why the applicant’s background and research goals are a strong fit for the group.
Before applying, prospective students should carefully review the X-Bai Research Group website and study its current research directions. This will help applicants prepare a more focused inquiry and demonstrate a genuine understanding of the group’s work.
Why This Opportunity Matters
For aspiring researchers interested in the future of space exploration and intelligent systems, this fully funded PhD opportunity offers a pathway to advanced research involving autonomy, artificial intelligence, robotics and space science.
Students may gain experience working on challenging questions involving orbit prediction, space situational awareness, robotic operations, machine learning and physics-informed approaches to complex space systems.
With opportunities available for Spring, Summer and Fall 2027 entry, interested candidates should begin preparing their academic and research materials early.
How to Apply: Interested applicants should prepare their CV, academic transcripts and a tailored statement demonstrating their research experience, technical contributions and alignment with the X-Bai Research Group. They should then contact Professor Xiaoli Bai directly and review the group’s official website for current research information and application guidance.
