Hybrid Boston Postdoc: AI & Multimodal Healthcare ML

Mass General Brigham; United States; Hybrid; USD 74,000 - 81,000; Full time

Benefits offered by this job

Mentorship program

Publication opportunities

Job summary

Mass General Brigham in Boston is seeking a postdoctoral fellow in AI and machine learning to develop original ML methods and shape their research direction in close collaboration with clinicians on meaningful healthcare problems.

The role offers opportunities to lead projects, publish findings, mentor junior researchers, and build an independent research agenda with clinical and computational mentorship, in a hybrid Boston-based setting.

Qualifications

• PhD in computer science, engineering, statistics, applied mathematics, physics, or a related quantitative discipline, completed before the appointment begins.
• Strong Python programming skills and hands-on experience developing and evaluating machine learning or deep learning models.
• Research expertise in at least one relevant area, such as physiological time-series analysis, signal processing, computer vision, representation learning, natural language processing, or multimodal learning.
• Evidence of original scientific contributions and the ability to lead a research project from question formulation through rigorous analysis and scientific communication.
• Strong communication skills, a collaborative approach, and an interest in interdisciplinary research.

Responsibilities

• Develop original ML methods and shape the research direction.
• Collaborate closely with clinicians on healthcare problems.
• Lead projects and publications; mentor junior researchers; develop an independent research direction.

Skills

Python programming

ML/DL experience

Original research

Time-series modeling

Computer vision

Representation learning

NLP

Multimodal AI

Communication skills

Education

PhD in CS/Engineering/Statistics/Math/Physics

Job description

Mass General Brigham in Boston is seeking a postdoctoral fellow in AI and machine learning to develop original ML methods and shape their research direction in close collaboration with clinicians on meaningful healthcare problems.

The role offers opportunities to lead projects, publish findings, mentor junior researchers, and build an independent research agenda with clinical and computational mentorship, in a hybrid Boston-based setting.