Massachusetts Eye and Ear

Post-Doctoral Research Fellow - Laryngology AI

Boston, MA, US$70,000-$71,750Posted 16 days ago

Job Description

Site: Massachusetts Eye and Ear Infirmary

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

The Postdoctoral Fellow will support and help lead a multidisciplinary research initiative focused on advancing laryngology through real-time machine learning, computer vision, and quantitative analysis of laryngoscopy videos. This role will involve developing, testing, validating, and translating algorithms that track laryngeal anatomy, classify examination states, extract clinically meaningful video-derived metrics, and support future clinical decision-support tools. The fellow will work with laryngologists, clinical research staff, engineers, and collaborators at Mass Eye and Ear and Mass General Brigham to move the project from proof-of-concept research toward reproducible, clinically useful deployment. This position is best suited for a highly independent, technically strong researcher with broad computer science or machine learning expertise who is interested in applying advanced AI methods to important clinical problems in laryngology. Qualifications

ESSENTIAL FUNCTIONS

 Data Collection & Processing

  • Extract, curate, and manage clinical research datasets, including flexible laryngoscopy videos, frame-level annotations, laryngeal keypoint data, high-fidelity voice recordings, operative data, patient-reported outcomes, and relevant clinical metadata.
  • Develop and maintain reproducible pipelines for video ingestion, annotation, quality control, de-identification, preprocessing, dataset ver...

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