Oculus Research's Surreal Vision team is looking for the next generation of scientists and engineers to tackle the most ambitious problems in machine perception. Multiple openings are now for available for interns throughout 2017 researching topics for new generations of augmented and virtual reality devices that have real-time scene-aware computing at their core.
- Geometric computer vision, tracking, reconstruction and SLAM systems
- Machine learning approaches to scene understanding
- Exotic sensor and computational imaging devices
- Large scale optimization and data science
- Software tools to enable totally new scales of mobile machine perception
- Full-stack AR systems and experiences for augmented and virtual reality
In particular we welcome PhD students wishing to work at the emerging intersection of geometric computer vision (e.g. reconstruction, tracking and mapping or SLAM research) and machine learning (e.g. deep learning for scene understanding, semantic segmentation or cross model learning), as well as students with a strong background in large scale or real-time optimization based computer vision. We also welcome students with a passion for working in a strongly collaborative team that spans research across algorithms, hardware design and systems prototyping.
Our internships are twelve (12) to twenty four (24) weeks long and we have various start dates throughout the year.
Oculus is proud to be an Equal 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, genetic information, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.
If you need assistance or an accommodation due to a disability, you may contact us at firstname.lastname@example.org or you may call us at +1 650-308-7837.