The Division of General Internal Medicine and Primary Care, Department of Medicine at Brigham and Women’s Hospital (BWH) and Harvard Medical School (HMS), invites applications for a postdoctoral fellowship in medical informatics. The Division is nationally recognized for providing compassionate, high-quality care, pioneering innovative medical education, and conducting cutting-edge clinical and health services research. We are seeking one highly motivated, diligent, and independent Research Fellow to join a dynamic research team supported by grants from the National Institutes of Health (NIH). This position focuses on advancing biomedical informatics research by applying artificial intelligence (AI) techniques and longitudinal electronic health records (EHRs) for disease phenotyping, risk factor identification, patient stratification, and predictive modeling. The successful candidate will design, develop, and evaluate innovative methods for data mining and analytics, leveraging comprehensive clinical knowledge bases, advanced natural language processing (NLP)/large language models (LLMs), and machine learning techniques. The ultimate goals are to drive knowledge discovery, improve clinical decision-making, enhance patient safety, and elevate the quality of care. The fellowship is based at Brigham and Women’s Hospital, Harvard Medical School, and Mass General Brigham, offering a collaborative, multidisciplinary environment at the forefront of health information technology research. Fellows will have the opportunity to engage in groundbreaking research, contribute to ongoing projects, and propose novel research initiatives with the potential to secure external funding. During the appointment period, Fellows will be strongly encouraged to publish their research findings in high-impact journals and present their work at national and international conferences. This opportunity is ideal for individuals who are both independently driven and collaborative, thriving in a vibrant research environment alongside a large team of experienced faculty and staff. Fellows must be comfortable giving and receiving constructive feedback, incorporating insights to improve their work, and transparently sharing their ideas and decision-making processes. Recognizing and valuing the contributions of colleagues is essential, as is the ability to communicate effectively within a diverse, multidisciplinary team.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree