At SafeBeat Rx (YC S21), we are building ECG software that literally saves lives and replaces a hospitalization. Our take-home kit allows patients to start heart meds safely at home, by combining FDA-cleared wearables with our ECG software that catches heart rhythm changes before they become heart attacks. Because we only focus on the software, our FDA and go-to-market pathways are much faster than other biotech/medtech companies. If you want to have a direct impact on millions of patients with heart problems, we'd love to connect. You would be working closely with the founders - two physician-engineers from Stanford/Harvard with a passion for medical innovation.

Read more at our bookface launch: https://bookface.ycombinator.com/posts/55104

Our research group in SafeBeat Rx makes life-saving ECG software technology, based on machine learning, that powers a hospital at home solution to replace certain types of cardiology admissions.

We are seeking a highly motivated Postdoctoral Fellow to join our research team. The ideal candidate will have a strong background in machine learning, artificial intelligence, or a related field and will contribute to ongoing projects while pursuing independent research interests.

This is an opportunity to attempt a really ambitious technology as part of a Silicon Valley Startup Company, SafeBeat.

About us

We are professional, agile, innovative and our goal is to make live saving software solutions that power a hospitalization at home for cardiology. We are backed by Y Combinator, 50 Years, and Fusion Fund.

Job Type: Full-time

Benefits: 401(k) Health insurance, PTO

Education: Doctorate (Preferred): C.S., E.E., E.E.C.S., Statistics, Mathematics, Physics

Experience: Scientific research: 3+ years (Required)

Work Location: Remote

Our codebase is in Python, React Native, and Django. Our ML models will be built in Tensorflow. Our software automates ECG measurements, recommends drug dosing, and catches rhythm changes before they become heart attacks. Doctors approve our algorithm’s measurements and dosing at every step for safety. Our interface aims for simplicity, based on what we wanted ourselves while treating patients.