Postdoctoral Fellow in AI/ML for Maternal and Perioperative Care

Location: Boston-MA

Site: The Brigham and Women's Hospital, Inc.

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.

Job Summary

APPLY BY EMAIL ONLY - APPLICATION INSTRUCTIONS BELOW.

About Our Lab

Help shape the future of AI for maternal and perioperative care. The Kovacheva Lab brings together clinicians, data scientists, and researchers to develop and evaluate computational approaches that improve care during pregnancy, childbirth, and the perioperative period. Our goal is to move rigorous scientific discoveries from model development through evaluation and integration into clinical workflows, including electronic health record– and device-based applications.

The Opportunity

We are seeking an ambitious, hands-on postdoctoral fellow with strong AI/ML expertise and demonstrated research accomplishments who is eager to lead original research with meaningful clinical impact. You will help shape the lab’s computational research directions and develop a distinctive research program, supported by clinical and technical mentorship and an existing clinical data platform.

Potential projects include physiological waveform modeling, AI for ultrasound and other medical imaging, multimodal learning, and early prediction of hypertensive crises, hemodynamic instability, and hemorrhage. Specific projects will be developed jointly around your strengths and interests, aligned with the lab’s clinical priorities and funded research aims. We welcome strong computational researchers from a range of fields. Prior experience in maternal health or perioperative medicine is not required, and candidates are not expected to have expertise across all listed data modalities.

You will have opportunities to work with a large-scale clinical data platform containing billions of data points from more than 300,000 patients, subject to applicable research, privacy, and data-governance approvals. You will formulate research questions, design rigorous experiments, develop and validate models, and lead manuscripts. The position offers opportunities to grow as an independent scientist, mentor junior colleagues, and collaborate with clinical and computational researchers across Mass General Brigham, Harvard Medical School, the Broad Institute, and industry.

A PhD in computer science, engineering, statistics, applied mathematics, physics, or another quantitative discipline, completed before the position start date.

Strong Python programming skills and hands-on experience developing and evaluating machine-learning or deep-learning models.

Demonstrated research expertise in machine learning or deep learning, with methodological strengths relevant to areas such as time-series modeling, computer vision, representation learning, or multimodal learning.

Evidence of scientific ownership, including leading a research project from question formulation through rigorous analysis and scientific communication.

Evidence of original research productivity, such as first-author peer-reviewed publications or substantial preprints.

Intellectual curiosity, clear communication, a collaborative approach, and interest in mentoring and interdisciplinary clinical research.