Machine learning is on the verge of transforming healthcare, and the MGH & BWH Center for Clinical Data Science (CCDS) is at the forefront of this revolution.
We are a fast-paced start-up embedded in two of the nation’s leading research hospitals, backed by industry partners like Nvidia and GE Healthcare.
We have access to millions of medical records, an on-prem GPU cluster, and a top-tier team from industry and academia. We work closely with clinicians to solve critical problems in patient care our goal is to make real products that make a real difference in the hospital.
The focus of our ML team is to build models that solve critical needs in healthcare. Classification to expedite treatment decisions, prioritize worklists, and improve diagnostic accuracy Segmentation and localization to improve the accuracy and speed of abnormality detection Volumetric assessment of pathologies, reducing clinician time per study thereby freeing them to focus on higher-
value tasks Time series analysis to predict outcomes based on streaming patient data
Fluent in Python Highly comfortable in one of Tensorflow, PyTorch, or Caffe2 Highly comfortable in the theory and practice of neural networks Highly comfortable with traditional machine learning algorithms (e.
g., SVM, boosting, bagging, etc.) Highly comfortable in SQL Comfortable working independently and defining measurable, achievable goals Experience shipping ML solutions in product Publications at top-
tier ML conferences (NIPS, ICML, ICLR, etc.) Experience writing production-grade software (code review, unit testing, integration testing, CI, etc.
Experience programming in C / C++ / Java / Go