Machine Learning in Healthcare Pre-Doctoral Fellow

Wanted:

Outstanding candidate for pre- doctoral machine learning fellowship at the Cardiovascular Imaging Research Center (https://www.massgeneral.org/imaging/research/cardiovascular-imaging-research-center) at Massachusetts General Hospital and Harvard Medical School.

The pre-doctoral fellow will participate 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.

Qualifications

- Master' s degree 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 plu

- Able to work in a collaborative team environment including MDs and PhDs

- Excellent communication skills

- Interest in academic manuscript authorship and grant writing