PhD Positions in Machine Learning, Nonlinear Dynamics, and Control (Spring or Fall 2026)
Applications are invited for two PhD positions in Electrical Engineering at Colorado State University in the interdisciplinary areas of Machine Learning (ML) in Nonlinear Dynamics and Control for the start date of Spring or Fall 2026. The Research areas are:
- AI and ML in Nonlinear Dynamical Systems
Data-driven models will be developed for tasks such as time-series prediction and the forecasting of extreme events in complex and dynamical systems.
- Hybrid Control Systems
Control strategies will be explored that combine machine learning methods with classical control theory to enhance adaptability, robustness, and system performance.
- Collective Behavior in Complex Dynamical Networks
Emergent phenomena such as synchronization and pattern formation will be studied in large-scale networks, with emphasis placed on applications in neuroscience (e.g., brain dynamics) and engineering (e.g., power and sensor networks).
Highly motivated applicants with experience in control and nonlinear dynamics and a strong background in mathematics are encouraged to apply. Applicants should have B.Sc. and M.Sc. degrees in Electrical Engineering or related fields. For qualified PhD candidates, the stipend and tuition will be provided. Continuation of financial support is contingent upon satisfactory academic/research performance and availability of funds.
To be considered, applicants are asked to submit the following documents:
- Curriculum Vitae (CV)
- Academic transcripts
- Contact information for two academic references
All application materials should be sent to Dr. Shirin Panahi:
S.Panahi@colostate.edu with the email subject line: Prospective PhD Student.
In your email, please briefly describe your relevant academic background, indicate which of the listed research areas you are most interested in, and your earliest availability to start.