Massachusetts Eye And Ear-posted 7 months ago
Full-time • Entry Level
Boston, MA

The Postdoctoral Fellowship in Medical AI is intended for graduates of doctoral programs in Science, Technology, Engineering, and Mathematics (STEM) with a solid foundation in applying advanced ML/AI techniques to tackle complex problems in healthcare. The program is ideal for early-career scientists seeking additional experience in the healthcare field, as well as opportunities to apply AI/ML technologies and software engineering to improve patient care and safety. The research fellow will be mentored by a multidisciplinary team of experts, allowing her/him to gain extensive knowledge and experience in diverse research areas including medicine, human factors, cognitive science, behavioral sciences, and aerospace and military research. The successful candidate will conduct research and development within the emerging field of medical AI, applying advanced programming and software engineering skills. The research fellow will design and develop software architectures and train and evaluate ML/AI models to create AI-based solutions and integrate them with large multi-source clinical databases, including time-series physiological data, demographics, behavioral and psychological assessments, video, audio, electronic health records (EHR), and clinical performance outcomes. The fellow will also develop AI-based medical simulation applications and real-time clinical decision support systems.

  • Conduct research and development in the field of medical AI.
  • Design and develop software architectures.
  • Train and evaluate ML/AI models.
  • Create AI-based solutions and integrate them with clinical databases.
  • Develop AI-based medical simulation applications.
  • Create real-time clinical decision support systems.
  • Ph.D. in a STEM discipline.
  • Proficiency in Python and/or C++.
  • Familiarity with signal processing and time series analysis.
  • Experience with cloud computing services and API.
  • Demonstrated experience with AI/ML training and model evaluations.
  • Experience with TensorFlow and/or PyTorch and/or Scikit-learn.
  • Prior experience in applying AI/ML in the medical field.
  • Research experience as lead author in peer-reviewed scientific publications.
  • Previous experience with computer vision (e.g., convolutional neural networks) and/or visual language models.
  • Comprehensive health insurance.
  • Optional dental and vision plans.
  • Retirement plans.
  • Reimbursement for conference travel related to fellowship projects.
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