Job Description
Description & Requirements
PARC, a Xerox company, is in the Business of Breakthroughs®. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. The Intelligent Systems Lab is unlike any organization in the world. Combine the best of an esteemed research organization, a topnotch university, an entrepreneurial startup, and a premiere technology company and you get ISL, a team that melds its world-class innovation chops with a focus on researching and developing real world applications that have market potential. Research in ISL focuses on computer vision, data science, computational design, artificial intelligence, knowledge engineering, with a focus on inferencing in diverse unstructured environments.
PARC’s Collaborative Visual Computing group is seeking a research scientist with expertise in computer vision, video analytics, and augmented reality to join an interdisciplinary team of researchers and engineers developing innovative applications in a variety of domains. Current activities include 2D/3D object detection and tracking, augmented reality for task assistance, human activity understanding, and medical image analysis. A common research theme is developing deep learning representations and models to perform visual tasks with very limited training data. This is an applied research position: we are seeking candidates interested in delivering innovations and results that will make real impact in the market. The ideal candidate approaches computer vision problems from a systems perspective, and extracts novel insights at the intersection of computer vision, computational imaging, sensing, and machine learning.S/he is a self-starter who will engage effectively with partners in commercial, academic, and government sectors to define and refine research directions, and to take ideas from the drawing board to prototype deployment. S/he also demonstrates a track record and interest to publish research in prestigious scholarly forums.
Responsibilities
- Lead and participate in R&D efforts to develop compelling computer vision applications with high market impact
- Work with other researchers and developers to turn novel concepts into demonstrable prototypes
- Actively engage with external academic, commercial, and government partners and clients to develop new research and business opportunities leveraging computer vision, including proposal development
- Author quality peer reviewed publications and inventions.
Candidates must submit a 1 page research statement summarizing research accomplishments, impact of the current work in the larger domain of computer vision and artificial intelligence, and envisioned future directions for the research.
Required Qualifications
- Ph.D. or equivalent experience in Electrical Engineering, Computer Science, or related fields, with specialization in computer vision and machine learning
- Strong quantitative/mathematical background
- Expertise in deep learning and associated frameworks, e.g. TensorFlow, PyTorch, Caffe, MXNet
- Hands-on algorithm and software development in one or more of Python, C/C++
- Excellent presentation and written communication skills
- The successful candidate must be able to meet the requirements under the International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR).
- Strong record of publications in high impact conferences and journals such as:
- IEEE Computer Vision and Pattern Recognition (CVPR) conference
- IEEE European Conference on Computer Vision (ECCV)
- IEEE International Conference on Computer Vision (ICCV)
- Neural Information Processing Systems (NIPS) Conference
- IEEE Winter Applied Computer Vision (WACV) conference
- IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
- IEEE Transactions on Image Processing
Desired Experience
- Computer vision for augmented reality, mobile and wearable devices
- Experience working with 3D data (point clouds, meshing, mapping)
- Video analysis, e.g. scene segmentation, summarization, action/activity recognition
- Multimodal sensing and learning methods
- Post-doctoral experience in an applied R&D setting working with other Ph.D.-level research scientists
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