Research Scientist Intern, Multimodal Learning for Robotics (PhD)
Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Oct 21, 2026. Meta scores B on the Alion truth index.
As a Research Scientist Intern, you will work at the intersection of robotic control, machine learning, and human-robot interaction, and you will have the opportunity to work with world-leading collaborators and mentors in these fields. Your primary focus will be on developing CV and tactile based algorithms that can be used for robotic control learning in dextrous manipulation tasks.
Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year. Some projects may require a minimum of 16 consecutive weeks.
Responsibilities
Conduct collaborative research on developing CV and tactile based algorithms for both human and robotics data. Develop robotic data pipelines for robotic dextrous manipulation, train models, and benchmark different algorithms. Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Qualifications
Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Robotics, or relevant technical field Experience in computer vision, with active contributions in at least one subdomain (3D reconstruction, hand pose estimation, object pose estimation) and strong familiarity across all Understand state of the art in robotic manipulation control policies, with experience in physics based simulators like Mujoco Experience with Python, PyTorch or JAX, or other related languages Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI), or similar Experience with multimodal learning including but not limited to tactile data Experience working with robot manipulation Experience with building pipelines with foundation CV models, for example, CLIP, DinoV2 or SAM2 Experience working and communicating cross functionally in a team environment Intent to return to the degree program after the completion of the internship/co-op Availability for minimum 16 consecutive week internship