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Nvidia Applied Research Intern Medical Imaging - Summer 2023 in Shanghai, China

NVIDIA is searching for world-class researchers in deep learning, focused on large-scale and high-precision medical imaging analysis, federated learning to join our applied research team. We believe that Deep Learning accelerated AI will completely reshape life sciences, medicine, and healthcare as an industry. To foster that transformation, NVIDIA is democratizing deep learning by providing an end-to-end AI computing platform crafted for the healthcare community.

GPU-accelerated deep learning solutions can be used to craft more sophisticated neural networks for healthcare and medical research applications: from real-time pathology assessment to point-of-care interventions to predictive analytics for clinical decision-making. Innovations in AI are advancing the future of precision medicine and population health management in spectacular ways. We are passionate about applying deep learning to healthcare applications for high-performance preventive/precision medicine, and knowledge mining from very large-scale clinical datasets and resources, to facilitate effective clinical workflows, built upon NVIDIA’s hardware/software AI platform. After building prototypes that demonstrate the promise of your research, you will collaborate with software engineering team to integrate your work into products.

What you'll be doing:

  • Craft DL approaches to solving medical imaging analysis, federated learning problems.

  • Construct and curate large problem datasets.

  • Design and implement medical imaging, computer vision, machine learning, federated learning techniques sought at solving specific problems.

  • Keep up with the latest DL research and collaborate with diverse teams, including DL researchers, physicians, hardware architects, and software engineers, etc.

  • Generate high-quality patents and top-tier technical or clinical publications, transfer technology into products.

What we need to see:

  • Pursuing a PhD in Electrical Engineering, Computer Science/Engineering, or related field.

  • Relevant work experience in computer vision, medical imaging, deep learning, statistical learning, federated learning.

  • You've produced a track record of research (publication) excellence and/or significant product development. IE 4+ pieces of tier-one publications with substantial deep learning for healthcare applications.

  • Excellent rapid prototyping skills with medical applications using Python.

  • Strong knowledge and development experience of common deep learning frameworks and packages (Caffe, Tensorflow, PyTorch, etc.).

  • Excellent communications skills.

  • Prior experience working with physicians to identify (novel) important problems and assessing possible DL solutions is a plus.

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, self-driving car powered by Artificial Intelligence can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. Many profound medical applications will improve humanity piece by piece via improved quality of healthcare with lower costs. This is truly an outstanding time. The era of AI has begun.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous researcher with a genuine passion for technology and improving the healthcare / medical industry? Come, join us and help build the real-time and high-quality computing platform driving our success in this exciting and quickly growing field.

THE WORLD LEADER IN VISUAL COMPUTING

NVIDIA’s invention of the GPU sparked the PC gaming market. The company’s pioneering work in accelerated computing—a supercharged form of computing at the intersection of computer graphics, high performance computing and AI—is reshaping trillion-dollar industries, such as transportation, healthcare and manufacturing, and fueling the growth of many others.

Learn more about NVIDIA (http://www.nvidia.com/object/about-nvidia.html#sthash.qlXKW56Q.dpuf) .

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