Post-doctoral training position in the lab of Dr. Geoff Tison, MD MPH, focusing specifically on applying artificial intelligence/machine learning methods to medical data for disease phenotyping and prevention. Post-doctoral and part-time positions available, minimum 1 year.
Dr. Tison, MD, MPH is a Cardiologist and Assistant Professor at the University of California, San Francisco (UCSF). His research focuses on cardiovascular prevention, using statistical and machine learning methods to analyze large-scale health data for disease prevention and phenotyping. He obtained formal training in machine learning, statistics, epidemiology and clinical research during his tenure at Johns Hopkins and as a National Institutes of Health T32 scholar. Dr. Tison received MD and MPH degrees from the Johns Hopkins Schools of Medicine and Public Health, completed internal medicine training at the Johns Hopkins Hospital, and fellowships in cardiology, advanced echocardiography and preventive cardiology at UCSF.
https://profiles.ucsf.edu/geoffrey.tison
https://ucsfhealthcardiology.ucsf.edu/facstaff/spotlight/tison
Ideal candidates will have an M.D. and/or Ph.D. with a strong background in computer science, data science, bioinformatics, computational biology, biostatistics or related fields. Strong understanding of biologic and medical sciences is preferred, but may not be required. A strong publication record in your respective field is encouraged.
Computational Requirements:
Demonstrated fluency in Python programming
Fluency with standard machine learning packages and frameworks including scikit-learn, tensorflow, pandas, keras, Pytorch.
Self-sufficiency to adopt new frameworks and languages as needed.
Please apply by filling out the following information and we will contact you shortly: https://www.surveymonkey.com/r/S8ZHMKT