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Machine Learning for Scene Understanding – Intern

Bosch Group

Machine Learning for Scene Understanding – Intern

Mountain View, CA +1 location
Internship
Paid
  • Responsibilities

    Company Description The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Human-Machine Intelligence (HMI), Robotics, Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design.The focus of our global research on Human Machine Collaboration includes Big Data Visual Analytics, Explainable AI, Audio Analytics, NLP, Conversational AI, Mixed Reality and Smart Wearables, etc. We develop intuitive, interactive and intelligent solutions to enable inspiring UX for Bosch products and services in application areas such as autonomous driving, car infotainment and driver assistance systems (ADAS), Industry 4.0 and Internet of Things (IoT), security systems, smart home and building solutions, health care, and robotics.As a part of our global research unit, our Mixed Reality and Autonomous Technologies group is responsible for shaping the future user experience of Bosch products by developing cutting-edge technologies and prototype systems in the field of mixed reality and robotics, including 2D/3D scene understanding, 3D reconstruction, augmented reality, robotics middleware (ROS2.0), AI-based manipulation, and human-robot collaboration. We focus on developing innovative solutions to address key challenges in computer vision, mixed reality, and robotics, for human machine collaboration in intelligent and autonomous systems. We work with internal partners of different Bosch business units to transfer our solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals, e.g. CVPR, ICCV, ICRA, ISMAR, ECCV, NeurIPS, AAAI, ICLR, TVCG, SIGGRAPH etc. Job Description * Conduct advanced R&D for machine learning/deep learning-based object and scene understanding (e.g., detection, segmentation, recognition).·         Apply research results to real-world use cases with high quality implementation. * Integrate the resulting system/software into existing Bosch platforms.* Summarize research findings in high-quality paper and/or patent submissions. Qualifications Basic Qualifications* Ph.D. students in Computer Science or Engineering* Major in computer vision, machine learning, and related fields.* Hands-on experience on developing perception algorithms, including deep learning approaches for detection, segmentation, tracking, recognition.* Solid C++ programming skill and/or python programming* Proficient with deep learning libraries (Pytorch, TensorFlow, MXNet, Caffe, etc)Preferred Qualifications* Publication record in top venues including CVPR, ICCV, ICRA, ISMAR, ECCV, NeurIPS, ICLR, TVCG, SIGGRAPH.* Experience in working with hardware systems including sensors such as RGBD cameras, depth sensors, IMU, LIDAR, etc.* Able to work independently, has strong research and problem-solving skills* Good communication and teamwork skills Additional Information * Major(s): Computer Science or related fields  * Degree level: Ph.D. or Master – Must be a current student or recent graduate (less than 1 year)  * Start Date: Summer 2021* Duration: 3 months By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives* FIRST Robotics (For Inspiration and Recognition of Science and Technology)* AWIM (A World in Motion)

  • Locations
    Mountain View, CA • Redwood City, CA