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Interested in robotics research?
Prospective Graduate Students
For the upcoming 2024-2025 application cycle, we will be looking to recruit multiple incoming Ph.D. students across all relevant departments (MEAM, ESE, or CIS). We are dedicated to assembling a dynamic and diverse team of researchers, and actively seek individuals with diverse cultural, ethnic, socioeconomic, and academic backgrounds.
Due to the volume of requests, I am not able to respond to all unsolicited emails from prospective graduate students. However, I strongly encourage you to apply through Penn graduate admissions to MEAM, ESE, or CIS and indicate my name on your application.
Postdoc Openings
We are always open to recruiting exceptional postdoctoral researchers in the area of data-efficient learning and control for dexterous manipulation. Postdocs will work with Prof. Posa and other students in the lab, and interact with industry research collaborators. The ideal applicant will have expertise in algorithmic development for robotic manipulation. Applicants should have publications in top robotics venues (RSS, ICRA, CoRL, TRO, IJRR, etc.).
Current Penn Students
Current Penn students are encouraged to apply for a research assistant position in the lab. Prospective lab members may be asked to participate for a period on a trial basis. Coursework or other experience in the some of following provides a useful background for the lab: controls (particularly in nonlinear and modern control), optimization, machine learning, robotics, linear algebra, programming (particularly Python and C++), and dynamics. The best preparation, particularly for seniors and masters students, would be to take MEAM 5170, typically taught in the fall by Michael.
Currently (last updated 7/2024), we are especially interested in recruiting current Penn undergraduate and masters students for the projects below.
- Software development of high-performance, real-time controllers. Students would collaborate with Ph.D. students to implement new control algorithms in C++, with a focus on high-performance, multi-threaded computation. Ideal candidates have experience with numerical optimization and C++ development.
- Design and fabrication for locomotion and manipulation experiments. Students would support experimentation for either locomotion (with the Cassie robot) or manipulation. Example projects include design and fabrication of a camera-based vision system or experimental apparatuses. Ideal students have design and fabrication experience.
- Physics-inspired machine learning. Students would collaborate with Ph.D. students to develop and test learning algorithms for robotic manipulation. Projects would involve software development and physical experimentation on a Franka Panda arm. Ideal students have experience with Python and machine learning.