Postdoctoral Fellow in AI/ML for Maternal and Perioperative Care
About The Position
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. 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.
Requirements
- 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.
Nice To Haves
- Experience with physiological waveforms, ultrasound, other medical imaging, or clinical data is welcome but not required.
Responsibilities
- Lead original research with meaningful clinical impact.
- Help shape the lab’s computational research directions.
- Develop a distinctive research program.
- Formulate research questions.
- Design rigorous experiments.
- Develop and validate models.
- Lead manuscripts.
- Grow as an independent scientist.
- Mentor junior colleagues.
- Collaborate with clinical and computational researchers.
Benefits
- J-1 visa sponsorship is available for eligible candidates, subject to institutional requirements.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
