"Postdoctoral Fellow in GPU-Accelerated Uncertainty-Aware Optimal Control"

Position Title:

Postdoctoral Fellow in GPU-Accelerated Uncertainty-Aware Optimal Control

Department:

Computer Science

Position Type:

Fellowship

Qualifications:

• PhD in Computer Science, Electrical Engineering, Robotics, Controls, or a closely related field; or ABD with degree received by the start date.
• Strong foundations in optimal control/optimization and software engineering
• GPU acceleration experience strongly preferred
• Real-world robotics/autonomy experience and robot learning are especially advantageous

This position is eligible for J-1 visa sponsorship for eligible candidates. Employment is contingent on authorization to work in the United States.

Application Instructions:

Please submit all materials electronically through Interfolio:

1. Cover letter, with a maximum of 2 pages, that includes research and teaching interests as well as preparation to serve Dartmouth's commitment to academic excellence in an environment that is welcoming to all;
2. Curriculum vitae, including names and contact information for three references;
3. One writing sample that showcases your previous research or closely aligns with the goals of this project.

Review of applications will begin immediately and will continue until the position is filled. Recommendation letters will be requested only for finalists. For questions about the position, please contact Professor Brian Plancher at plancher@dartmouth.edu.

Description:

The Department of Computer Science at Dartmouth College invites applications for a postdoctoral researcher with expertise in the area of GPU-Accelerated Uncertainty-Aware Optimal Control.

This project is housed in the Accessible and Accelerated Robotics (A2R) Lab led by Professor Brian Plancher and is a joint project with Thomas Lew and the rest of the Human Interactive Driving team at the Toyota Research Institute (TRI). This project focusses on real-time, uncertainty-aware optimal control, targeting autonomous driving at the limits of handling, with validation on high-performance vehicles.

Research topics may include (but are not limited to):

• Novel (stochastic) optimal control algorithms and methods
• Structure-exploiting numerical optimization solvers
• Differentiable optimization
• High-performance GPU implementations
• Hybrid gradient-, sampling-, and learning-based methods
• System integration and design for real-world deployments in dynamic environments

This position is full-time, non-remote, in-residence at Dartmouth College in Hanover, NH, with start date as early as April 2026. Appointments are typically for a 1-year period and renewable up to 3 years total. Postdoctoral researchers are advised and hosted in the Department of Computer Science. They are also supported by the Guarini School for Graduate and Advanced Studies, including their community initiatives.

Dartmouth is committed to academic excellence and encourages the open exchange of ideas within a culture of mutual respect. Dartmouth welcomes people with different backgrounds, life experiences, and perspectives and believes that diversity in all its forms enhances academic excellence. Applicants should address in their materials how their research, teaching, service, and/or life experiences prepare them to serve Dartmouth's commitment to academic excellence in an environment that is welcoming to all.

EEO Statement:

Dartmouth College is an equal opportunity employer under federal law. We prohibit discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications are welcome from all.

Dartmouth is committed to accessibility for its community. If you are an applicant with a disability and would like to request a reasonable accommodation to aid in the job application and/or interview process, please email: ADA@Dartmouth.edu. In the subject line, please state application accommodations and include the job number or title. Someone from the ADA/504 Office will be in touch within 2 business days.