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Summary:

At Reality Labs Research, our goal is to explore, innovate and design novel interfaces and hardware for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of natural, seamless experiences in XR environments that are effective, enjoyable, and functionally indistinguishable from those in the real world. 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.

Required Skills:

Research Scientist Intern, Multimodal Learning for Robotics (PhD) Responsibilities:

1. Conduct collaborative research on developing CV and tactile based algorithms for both human and robotics data.

2. Develop robotic data pipelines for robotic dextrous manipulation, train models, and benchmark different algorithms.

3. Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.

Minimum Qualifications:

Minimum Qualifications:

4. Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Robotics, or relevant technical field

5. 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

6. Understand state of the art in robotic manipulation control policies, with experience in physics based simulators like Mujoco

7. Experience with Python, PyTorch or JAX, or other related languages

8. Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications:

Preferred Qualifications:

9. 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

10. Experience with multimodal learning including but not limited to tactile data

11. Experience working with robot manipulation

12. Experience with building pipelines with foundation CV models, for example, CLIP, DinoV2 or SAM2

13. Experience working and communicating cross functionally in a team environment

14. Intent to return to the degree program after the completion of the internship/co-op

15. Availability for minimum 16 consecutive week internship

Public Compensation:

$7,650/month to $12,134/month + benefits

**Industry:** Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].