This robotics residency program is a full-time position for 18 to 24
months. We expect the residents to gain the technical knowledge and
practical expertise of AI and robotics research throughout the residency.
This program is designed to prepare them for the subsequent graduate study
or kickstart a career in the AI and robotics industry. We are looking for
people with both a strong experience of building real robotics systems and
a deep enthusiasm for artificial intelligence. Accepted residents will be
based on Stanford campus, and will work together with researchers in SVL to
develop hardware systems and AI algorithms for a variety of robot platforms.
1. Design and manage hardware infrastructure for real-world robot learning
2. Identify mechanical challenges and prototype solutions in CAD;
3. Read AI and robotics textbooks and publications and implement prior work
into high-quality code;
4. Collaborate with SVL researchers to conduct novel research and publish
papers in top-tier conferences.
1. Bachelor or master degree in CS, EE, or ME, or equivalent experience;
Ph.D.’s with good software engineering skills will also be considered.
2. Familiarities of common topics in robotics and control, such as
controller design, planning, state estimation, robot kinematics & dynamics,
3. Strong coding skills in Python and C++;
4. Great communication skills and strong passions about AI and robots;
5. Permission to work legally in the United States during the residency
period; Stanford and SVL will not provide assistance in obtaining work
permits or visa.
Prior exposure to machine learning and computer vision/robotics research;
Experience in machine learning (TensorFlow, PyTorch,..), robotics and
computer vision software (ROS, PCL, OpenCV, etc);
Experience with mechanical design and prototyping.
To apply, please submit the following materials:
1. A resume that highlights your relevant experience in robotics;
2. A cover letter outlining the reason why you are interested in this
3. Transcript from the most recent degree;
4. (Optional) Two letters of recommendation.
For application and other inquiries, please contact Yuke Zhu (