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Meta AR/VR Job | Research Scientist Intern, Machine Perception & Learning (PhD)

Job(岗位): Research Scientist Intern, Machine Perception & Learning (PhD)

Type(岗位类型): 3D Software Engineering | Computer Vision, Machine Learning, Research

Citys(岗位城市): Redmond, WA

Date(发布日期): Before 2021-12-14

Summary(岗位介绍)

The Facebook Reality Labs (FRL) Research Team brings together world-class researchers, developers, and engineers to create the future of AR and VR. These technologies have the potential for enormous global impact, and our interns work directly towards making this potential a reality. The Surreal Vision team is looking for research interns to tackle the most ambitious problems in machine perception.

In this internship, you will work on research problems at the forefront of industry and academia and beyond. You will be working with a team building a new generation of end-to-end real-time dynamic 3D scene understanding and photorealistic reconstruction systems. The range of topics in machine learning, computer vision and graphics span novel approaches to 3D object detection and tracking, 3D human pose estimation, tracking, and forecasting, detailed scene geometry, lighting, material estimation, and photo-realistic scene synthesis, and contextualized AI.

Our internships are twelve (12) to twenty four (24) weeks long and you have the option to start at various dates throughout the year.

Qualifications(岗位要求)

Currently has, or is in the process of obtaining, a PhD in the field of Computer Science, Computer Vision, Machine Learning, Robotics, Physics or related fields

Experience in one or more of the following: machine learning, perception, information theory, 3D geometry, 3D reconstruction, graphics, tracking, Bayesian inference, optimization, system building, physics-based simulation

Experience with C++ or Python

Experience with deep learning frameworks such as PyTorch, Tensorflow, etc.

Interpersonal experience: cross-group and cross-culture collaboration

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

Description(岗位职责)

Fundamental research and development of ideas that extend the state of the art

Analysis and improvement of efficiency, accuracy, scalability and stability of currently deployed systems

Design and implementation of algorithms

Development and analysis of prototype experimental systems

Collaboration with and support of other researchers across various disciplines

Communication of research agenda, progress and results

Additional Requirements(额外要求)

Broad understanding of the full machine vision pipeline from sensors to high-level algorithms

Experience in research targeting the foundations of computer vision, machine learning and computer graphics

Experience in cutting-edge research in photorealistic reconstruction of scenes, objects and materials, neural light field reconstruction, inverse graphics and related rendering approaches

Experience in current research on object shape embedding, detection and tracking in 2D and 3D

Experience in state-of-the-art research on high fidelity human and object pose estimation, joint object-based reconstruction and tracking with human and scene interactions

Experience in modern machine-learning methods for self-supervised learning, federated learning, video-understanding, GANs, reinforcement learning

Experience in the latest techniques in computational imaging and computational photography

Experience in techniques and research in the emerging field of egocentric computer vision

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 CVPR, ECCV/ICCV, BMVC, NeurIPS, ICML, ICLR, ICRA, IROS, RSS or SIGGRAPH/SIGGRAPH Asia

Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)

Intent to return to degree-program after the completion of the internship

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