Research Intern - Biomedical AI for Precision Health

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. The advent of big data heralds a new era of precision healthcare, where medicine is tailored to individuals, reducing cost, suffering, and missed treatment opportunities. Artificial intelligence (AI) can play a key role in this transformation by discerning knowledge from data and separating signal from noise. We aspire to advance AI toward developing health systems that can instantly incorporate any new information to optimize delivery and accelerate discovery. A key bottleneck is that current health systems are mired in overwhelming unstructured data and non-scalable manual processing. Recent advances in generative AI, such as large language models (LLMs), offer unprecedented “universal structuring” capabilities that can supercharge health information processing and unlock many high-value applications in real-world evidence and precision health. Microsoft Research is an interdisciplinary team of scientists, engineers, and medical doctors who endeavor to develop next-generation AI for precision healthcare. We offer a unique vibrant environment that features cutting-edge academic research, enterprise software development, and real-world delivery, with close feedback loops and rapid iterations among all three, much like a lean startup. We are looking for an innovative, collaborative Research Intern to join our efforts at the intersection of AI and healthcare, where we partner with premier medical centers and develop state-of-the-art deep learning, natural language processing (NLP), and multi-modal technologies to extract knowledge from tens of millions of research publications, distill patient information from hundreds of millions of electronic health records (EHRs), and assimilate them with billions of genomics data points to support biomedical research and clinical decision making.