Internship Openings

MERL is seeking a highly motivated and qualified intern to conduct research on human-robot interaction. There are several research topics of interest, including foundation models, shared autonomy, object handovers, learning from feedback, and safety in close proximity. Applicants must be Ph.D. students with strong backgrounds in robot learning or computer vision. The selected intern will collaborate closely with MERL researchers to design and implement novel algorithms, conduct experiments, and disseminate research findings through a top-tier conference. The start date and duration are flexible, and interested applicants are encouraged to apply with an updated CV and a list of relevant publications.

Required Specific Experience

• Demonstrated experience in human-robot interaction, robot learning, or vision-language models
• Experience with ROS2, Python, and deep learning frameworks such as PyTorch
• Current enrollment in a Ph.D. program
• A strong publication record or demonstrated research potential

The pay range for this internship position will be 6-8K per month.

MERL is seeking a highly motivated and qualified intern to conduct research on robotic disassembly. There are several research topics of interest, including task and sequence planning, learning skills, perception under occlusion, contact-rich manipulation, and vision-language models for acting under uncertainty. Applicants must be Ph.D. students with strong backgrounds in robot learning or computer vision. The selected intern will collaborate closely with MERL researchers to design and implement novel algorithms, conduct experiments, and disseminate research findings through a top-tier conference. The start date and duration are flexible, and interested applicants are encouraged to apply with an updated CV and a list of relevant publications.

Required Specific Experience

• Demonstrated experience in computer vision, robot learning, or vision-language models
• Experience with ROS2, Python, and deep learning frameworks such as PyTorch
• Current enrollment in a Ph.D. program
• A strong publication record or demonstrated research potential

The pay range for this internship position will be 6-8K per month.

MERL is looking for a self-motivated intern to work on problems at the intersection of multimodal large language models and embodied AI in dynamic indoor environments. The ideal candidate would be a PhD student with a strong background in machine learning and computer vision, as demonstrated by top-tier publications. The candidate must have prior experience in designing synthetic scenes (e.g., 3D games) using popular graphics software, embodied AI, large language models, reinforcement learning, and the use of simulators such as Habitat/SoundSpaces. Hands on experience in using animated 3D human shape models (e.g., SMPL and variants) is desired. The intern is expected to collaborate with researchers in computer vision at MERL to develop algorithms and prepare manuscripts for scientific publications.

Required Specific Experience

• Experience in designing 3D interactive scenes
• Experience with vision based embodied AI using simulators (implementation on real robotic hardware would be a plus).
• Experience training large language models on multimodal data
• Experience with training reinforcement learning algorithms
• Strong foundations in machine learning and programming
• Strong track record of publications in top-tier computer vision and machine learning venues (such as CVPR, NeurIPS, etc.).

MERL is seeking a self-motivated and highly qualified Ph.D. intern to contribute to the development of a safety-oriented active SLAM system for aerial robots. The work will involve the development of perception-aware safe planning algorithms, along with extensive validation in both simulation and on hardware, using drones equipped with onboard cameras.

The intern will work closely with MERL researchers in robotics and autonomy. The internship is expected to lead to a publication in a top-tier robotics, computer vision, or control conference and/or journal. The position has a flexible start date (Summer/Fall 2026) and a duration of 3–6 months.

Required Specific Experience

• Current enrollment in a Ph.D. program in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Computer Science, or a closely related field, with a focus on Robotics, Computer Vision, and/or Control Systems.
• Hands-on experience with aerial robots, including real-world flight testing.
• Expertise in one or more of the following areas: active SLAM; 3D computer vision; coverage path planning; multi-agent pathfinding; perception-aware planning.
• Excellent programming skills in Python and/or C++, with prior experience using ROS2 and high-fidelity simulators such as Isaac Sim and/or MuJoCo.
• A strong publication record or demonstrated research potential in leading computer vision or robotics venues, such as ICRA, IROS, RSS, RA-L, T-RO, CVPR, ECCV, ICCV, or NeurIPS.

Preferred Experience

• Strong software engineering skills, demonstrated through a publicly accessible codebase (e.g., GitHub or GitLab). Applicants are required to provide links to representative repositories.
• Experience with onboard perception, visual-inertial systems, or safety-critical autonomy.
• Familiarity with trajectory optimization, MPC, or optimization-based control for robots.

The pay range for this internship position will be 6-8K per month.