Explore This Fellowship

Overview

PhD Postdoctoral Machine Learning in Healthcare Fellow

Outstanding PhD for postdoctoral machine learning fellowship at the Cardiovascular Imaging Research Center at Massachusetts General Hospital and Harvard Medical School.

The fellow will lead deep learning projects to predict cardiovascular health outcomes (heart attack, stroke) from routine medical imaging (retinal fundoscopy, chest/coronary computed tomography). We then aim to use multi-omics data and interpretability techniques to understand what biological processes these models are capturing. This will be accomplished in high quality datasets of tens of thousands of individuals with imaging, genomics, and adjudicated outcomes (Framingham Heart Study (Hoffmann U et al. JAMA Cardiology 2017); Jackson Heart Study (Sempos et al Am J Med Sci 1999); The Mass General Brigham Biobank (Boutin et al. 2022 J Pers Med); the National Lung Screening Trial (NEJM 2011); and the UK Biobank (Sudlow et al. 2015 PLoS Medicine).

The program is well funded with a track record of academic productivity and grant funding for fellows. Our research has been featured on CNN Health, Fox News, and various medical news outlets.

Representative publications:

Deep learning of the retina enables phenome and genome-wide analyses of the microvasculature

Validation of a deep learning-based model to predict lung cancer-risk using chest radiographs and electronic medical record data

Deep learning to predict mortality after cardiothoracic surgery using preoperative chest radiographs

Recent media coverage:

https://www.foxnews.com/health/ai-model-could-help-predict-lung-cancer-risks-non-smokers-study-finds-significant-advancement

https://www.cnn.com/2022/11/29/health/heart-attack-stroke-x-ray/index.html

Job Experience

  • PhD in computer science, computational biology, or related quantitative field
  • Experience in python programming and deep learning frameworks (PyTorch and/or TensorFlow)
  • Background in medical imaging or computer vision is a plus
  • Background in genomics, especially GWAS studies, is a plus
  • Able to work in a collaborative team environment including MDs and PhDs
  • Excellent communication skills
  • Interest in academic manuscript authorship and grant writing

How to Apply

Interested candidates should send a copy of their CV, a personal statement, and three letters of reference to Yuji Liao, Sr. Administrative Manager, and Vineet Raghu, Principal Investigator.