Postdoctoral Fellowship in Data Science and Artificial Intelligence at Johns Hopkins University
The Johns Hopkins Data Science and AI (DSAI) Institute is inviting applications for its prestigious postdoctoral fellowship program. This opportunity is designed for scholars from diverse disciplinary backgrounds who are passionate about advancing foundational methods in data science and artificial intelligence, as well as their applications in fields such as science, health, medicine, engineering, policy, governance, democracy, and ethics. Fellows will join a vibrant research community at Johns Hopkins University, collaborating with a broad array of faculty members and contributing to the institute's research, education, policy, and outreach missions.
The DSAI Institute is rapidly expanding, featuring a state-of-the-art facility on the Homewood campus and enhanced computing resources, positioning Johns Hopkins as a leading academic hub for data science and AI. The postdoctoral fellowship is a two-year position with the possibility of extension, offering a competitive salary, academic travel stipend, mentoring by DSAI-affiliated faculty, and access to advanced computational infrastructure. Fellows will participate in center-supported educational initiatives and projects, forming a cohort of outstanding scholars dedicated to shaping the future of data science and artificial intelligence.
Applicants should hold a PhD in a relevant field such as data science, artificial intelligence, computer science, engineering, or related disciplines. The program encourages candidates with interdisciplinary backgrounds and a strong research record. No specific GPA or language test requirements are mentioned. The application deadline is January 23, 2026, but applications may be considered after this date until all positions are filled.
To apply, visit the DSAI Institute's official website and follow the application instructions. For further inquiries, contact [email protected]. This is an excellent opportunity for early-career researchers to advance their expertise in data science, AI, machine learning, computer vision, medical imaging, healthcare, policy, governance, and ethics at one of the world's leading research universities.