Computer Science Research Fellow
Mass General Brigham · Boston-MA
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Read the full posting as the employer wrote it
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
We are looking for a PhD post-doctoral Fellow, or PhD candidate with background and interest in machine learning generally and medical image processing specifically to join our group. We are currently funded by NIH & Philanthropic funding to work on applications of deep learning and conventional image analysis techniques to medical images and text (i.e., multi-modal learning). The clinical focus of our current projects are (1) to assist radiologists in detection and classification of vascular abnormalities on brain CT angiography (CTA) images acquired at MGB-BWH, and (2) to assist radiologists in reducing error during interpretation of brain CT and MRI through large language model summarization of text in the medical record.Our Group: We are a multi-institutional research team composed of faculty from Harvard Medical School (HMS) (GY, JK, LQ), Mass General Brigham (MBG) Brigham and Women's Hospital (BWH) (GY, JK), Dana Farber Cancer Institute (DFCI) (GY, LQ, JK), and the Khoury College of Computer Sciences at Northeastern University (NU) (BW, HJ).
Qualifications
IMPORTANT – APPLICATION INSTRUCTIONS
This is a courtesy posting. Please do not submit your application through the Workday "Apply" button.
To be considered for this position, email your CV and cover letter describing your research interests and goals, a full list of publications to the hiring manager Kizzy Scott at kscott9@bwh.harvard.edu
Applications submitted only through Workday will not be forwarded to the hiring manager and may not be reviewed.
Key Responsibilities:
Specific Duties: The candidate will work closely with professors Geoffrey Young MD (Neuroradiology), Jisoo Kim MD (Neuroradiology), Lei Qin PhD (Medical Physics and Image Processing), Byron Wallace PhD (Computer Science and NLP AI) and Huaizu Jiang PhD (Computer Science and Computer Vision AI) on machine learning, medical image processing and multi-modal modeling. The work will include data acquisition, pre-processing and segmentation, as well as using natural language processing on medical text data. This will include implementation and extension of current state-of-the-art deep learning models (typically in Python). Experience with "conventional" image processing techniques (especially as used in radiological imaging) a plus, but not required.
QUALIFICATIONS:
- Experience with Computer Vision and/or Medical Image Processing
- Experience with deep learning/AI models is a plus.
- PhD in Computer Science or Equivalent Discipline preferred.
Additional Job Details (if applicable)
The compensation range for this role is between $71,750 - $81,179. Candidate experience is thoughtfully considered throughout the recruitment process, and those with significant experience may be considered for compensation above the starting range listed, as consistent with organizational guidelines and internal equity
Years of experience
0 $71,750 - $73,544
1 $73,544 - $75,382
2 $75,382 - $77,267
3 $77,267 - $79,199
4+ $79,199 - $81,179
Remote Type
Work Location
EEO Statement:
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.
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