Postdoctoral Fellow in Machine Learning and Multimodal AI Brigham and Women's Hospital in United States

The Kovacheva Lab at Brigham and Women’s Hospital and Harvard Medical School in Boston is recruiting a Postdoctoral Fellow in Machine Learning and Multimodal AI. This is a full-time, temporary postdoctoral position in an interdisciplinary clinical research environment connected to Mass General Brigham and the Department of Anesthesiology.

The role is ideal for a strong, independent computational researcher interested in developing original machine learning methods and shaping a research direction around meaningful healthcare problems. The lab’s research spans physiological signals, medical imaging, clinical text, and electronic health records, with applications in maternal and perioperative medicine. Potential topics include physiological time-series modeling of ECG, PPG, hemodynamic waveforms, and irregularly sampled clinical data; computer vision and representation learning for ultrasound and other imaging modalities; multimodal learning that combines signals, images, text, and structured records; and robust, trustworthy ML for clinical prediction tasks.

A distinguishing feature of the position is the lab’s combination of close clinical collaboration, access to large-scale real-world clinical datasets, and established research infrastructure. The team has developed MERLIN, a scalable platform for clinical data processing and reproducible dataset generation, supporting research on complex heterogeneous healthcare data. The postdoctoral fellow will have opportunities to formulate original research questions, lead projects and publications, mentor junior researchers, and develop an independent research direction with both clinical and computational mentorship.

Eligibility highlights: applicants must hold a PhD in computer science, engineering, statistics, applied mathematics, physics, or a related quantitative discipline before the appointment begins. Strong Python programming skills and practical experience with machine learning or deep learning are required. The lab especially values rigorous experimental design, careful model evaluation, scientific publication experience, and expertise in at least one relevant area such as time-series modeling, computer vision, representation learning, NLP, or multimodal AI. Prior healthcare experience is not required, and the position welcomes international applicants. J-1 visa sponsorship is available for eligible candidates.

Funding and appointment: the research program has five years of funding. The initial appointment is for one year and may be renewed annually subject to satisfactory performance and institutional requirements. The advertised salary range is USD $73,544–$81,179 per year, depending on experience and institutional policy.

Application window: applications are reviewed on a rolling basis, with a deadline of 31 December 2026. Applicants should email a CV, a brief cover letter describing research interests and key scientific contributions, and links to one or two representative publications or preprints, together with anticipated start availability.