Postdoctoral Research Fellowship – Medical Artificial Intelligence

Mass General Brigham • Boston, MA

7d • Hybrid

About The Position

The NEIL AND ELISE WALLACE STRATUS Center for Medical Simulation at Brigham and Women's Hospital is hiring a full-time, 40-hour-per-week hybrid postdoctoral research fellow for the Medical AI & Cognitive (MAICE) Lab. The fellowship prepares researchers to bridge artificial intelligence and clinical care through interdisciplinary research applying AI and machine learning to improve clinician performance, patient safety, and clinical outcomes. Research settings include emergency medicine, critical care, surgery, space, and military medicine. The position has no clinical duties.

Applicants may apply to one of two tracks. The Computational Track is for graduates of doctoral programs in STEM with experience applying advanced AI/ML techniques; fellows develop software architectures and data pipelines, train and evaluate models, and integrate AI with clinical databases and clinical or simulation environments. The Clinician-Scientist Track is for clinicians with research experience and an interest in medical AI; fellows translate clinical problems into research, conduct simulation-based and clinical studies, establish clinical ground truth, and evaluate AI systems. Fellows in both tracks work with large, multimodal clinical datasets and contribute to AI-based simulation applications and real-time clinical decision support.

Fellows receive multidisciplinary mentorship and follow an individualized development plan. Support includes first-author publications, national and international conference presentations, and applications for independent fellowships and career development awards. The appointment is for two years, with the possibility of renewal for a third and/or fourth year, subject to performance review and funding. The selected candidate may be eligible for an appointment at Harvard Medical School.

Requirements

• Doctoral degree (Ph.D., M.D., or equivalent) completed by the start date.
• At least three peer-reviewed publications as a significant contributor, including at least one as lead author. Journal articles and full-length peer-reviewed conference papers count.
• Strong interest in a research career at the intersection of AI and medicine.
• Excellent written and verbal communication skills and ability to work effectively in multidisciplinary teams.
• Computational Track: Ph.D. in a STEM discipline, such as computer science, electrical or biomedical engineering, data science, or statistics.
• Computational Track: Proficiency in Python and/or C++.
• Computational Track: Demonstrated experience training and evaluating AI/ML models, including neural networks and/or large language models.
• Computational Track: Demonstrated experience with PyTorch and/or TensorFlow and/or scikit-learn.
• Computational Track: Familiarity with signal processing and time-series analysis.
• Clinician-Scientist Track: M.D., D.O., Ph.D., or equivalent clinical degree.
• Clinician-Scientist Track: Demonstrated clinical research experience, including study design, data collection, and statistical analysis.
• Clinician-Scientist Track: Hands-on experience analyzing research data using R, Python, Stata, SAS, or a similar tool.
• Clinician-Scientist Track: Demonstrated engagement with AI, data science, or digital health, such as an AI/ML research project, an evaluation of AI tools or large language models, or relevant coursework or certification.

Nice To Haves

• Computational Track: Prior experience applying AI/ML to medical or health data.
• Computational Track: Experience with computer vision, such as convolutional neural networks, and/or vision-language models.
• Computational Track: Familiarity with cloud computing services and APIs.
• Computational Track: Experience with multimodal data, such as video, audio, and physiological signals, or real-time systems.
• Clinician-Scientist Track: Completed residency or other clinical training, especially in emergency medicine, critical care, anesthesiology, or surgery.
• Clinician-Scientist Track: Advanced training in research methods, epidemiology, biostatistics, or informatics, such as an MPH, MS, MMSc, or Ph.D.
• Clinician-Scientist Track: Programming experience in Python, including use of machine-learning libraries.
• Clinician-Scientist Track: Experience writing IRB protocols, conducting prospective data collection, or conducting healthcare simulation research.

Responsibilities

• Conduct medical AI research and development, from study design through publication, in areas including emergency medicine, critical care, surgery, space, and military medicine.
• Work with large, multi-source clinical datasets, including physiological time-series data, demographics, behavioral and psychological assessments, video, audio, electronic health records, and clinical performance outcomes.
• Contribute to development and evaluation of AI-based medical simulation applications and real-time clinical decision support systems.
• Lead first-author manuscripts and conference presentations and contribute to grant proposals.
• Collaborate with clinicians, engineers, and scientists, and help mentor students and junior team members.
• Computational Track: Design and develop software architectures and data pipelines for AI-based solutions.
• Computational Track: Train, fine-tune, and evaluate machine-learning and AI models, including neural networks, large language models, and computer vision models.
• Computational Track: Integrate AI models with large clinical databases and deploy them in simulation and real-time clinical environments.
• Clinician-Scientist Track: Identify clinically meaningful problems and translate them into AI research questions and study designs.
• Clinician-Scientist Track: Design and conduct simulation-based and clinical studies, including writing IRB protocols and leading data collection.
• Clinician-Scientist Track: Define clinical ground truth, including expert annotation of video, audio, physiological, and EHR data.
• Clinician-Scientist Track: Evaluate AI systems, including large language models, for clinical accuracy, safety, bias, and usability, and study clinician interaction with AI tools.
• Clinician-Scientist Track: Build practical data-analysis, programming, and AI skills through mentored projects and available training.

Benefits

• Comprehensive health insurance.
• Optional dental plan.
• Optional vision plan.
• Optional retirement plans.
• Reimbursement for conference travel related to fellowship projects.
• Potential eligibility for an appointment at Harvard Medical School.
• Mentorship and individualized development support, including support for publications, conference presentations, and applications for independent fellowships and career development awards.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree