Applied Research Intern, Medical Imaging - Summer 2024

NVIDIA is seeking 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 firmly believe that Deep Learning accelerated AI will entirely reshape life sciences, medicine, and healthcare industry. To promote this transformation, NVIDIA provides an end-to-end AI computing platform specially designed for the healthcare community. GPU-accelerated deep learning solutions can be employed to develop more advanced neural networks for healthcare and medical research applications, ranging from real-time pathology assessment to point-of-care interventions, to predictive analytics for clinical decision-making. AI innovations are shaping the future of precision medicine and population health management in unprecedented ways. We are passionate about leveraging deep learning for healthcare applications for high-performance preventive/precision medicine, and knowledge extraction from enormous clinical datasets and resources, to streamline effective clinical workflows, constructed on NVIDIA’s hardware/software AI platform. After constructing prototypes that validate your research, you'll work with software engineering team to incorporate your work into products. What you'll be doing: - Develop Deep Learning approaches to solve medical imaging analysis, federated learning problems. - Create and curate large problem datasets. - Design and implement medical imaging, computer vision, machine learning, federated learning techniques aimed at solving specific problems. - Remain updated with the latest Deep Learning research and collaborate with diverse teams, including Deep Learning researchers, physicians, hardware architects, and software engineers. - Produce high-quality patents and premier 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, federated learning, multi-modality model, generative AI. - Track record of research excellence and/or significant product development. E.g., 4+ pieces of tier-one publications with substantial deep learning for healthcare applications. Ways to stand out from the crowd: - Excellent rapid prototyping skills with medical applications using Python. - Proficient knowledge and development experience of common deep learning frameworks and packages (Caffe, Tensorflow, PyTorch, etc.). - Prior experience in building foundation model using a large amount of data is a plus. Today, AI-powered machines that can learn, reason, and interact with people are no longer a scenario from science fiction. Currently, a self-driving car powered by Artificial Intelligence can navigate a country road at night. An AI-powered robot learns motor skills through trial and error. Innumerable profound medical applications will progressively improve healthcare quality with reduced costs. We are witnessing a historic time, the era of AI has begun. NVIDIA is widely recognized as one of the most desirable employers in the tech world. We hire some of the most innovative and hardworking individuals globally. If you are a creative and autonomous researcher genuinely passionate about technology and improving the healthcare / medical industry, we welcome you to join us in driving our success in this exciting and rapidly growing field. Our interns receive an hourly rate between 19 USD - 93 USD. This standard pay is determined based on the position, your location, year in school, degree, and experience. You will also be eligible for intern benefits. NVIDIA accepts applications on an ongoing basis. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, our hiring and promotion practices don't discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.