The lab of Dr. Euan Ashley is seeking a highly motivated data scientist for a funded 1-year postdoctoral scholar position focused on analysis of data from wearable and mobile health data platforms collected over the past 5 years as part of the My Heart Counts study.
Our laboratory lives within the Departments of Medicine (Cardiovascular Medicine), Genetics, and Biomedical Data Science. Dr. Ashley’s research focuses on leveraging emerging technologies such as genomics and wearable sensors to provide insights into precision medicine (ashleylab.stanford.edu/).
Our team runs the My Heart Counts study, an iOS app-based survey of activity and health with data from over 60,000 participants from 3 continents. The study was launched in 2015, at the same event as the Apple Watch, and has since been used to find insights into cardiovascular health, create a data portal and complete an entirely remote randomized controlled trial to promote physical activity.
The role of postdoctoral scholar will focus on completing statistical analysis of the emerging results from our randomized trial, which now includes mindset measures, as well as data science for a contemporary data portal. This should not be your first rodeo — our data are messy with many edge cases and lots of missingness, areas that will need careful consideration. Types of data collected and ready for analysis include surveys, mobile analytics, CoreMotion (activity state detection, pedometer), sensor (accelerometer, GPS), device (HealthKit) and HealthRecords (EMR). Depending on interest, you may also help launch a follow-on study, which is slated to be released in 2022 on iOS and Android. In addition to strong programming and data science skills, you should have an empathetic mindset towards the user and be able to think about the impact of user experience and technical issues on the data. You will present findings within Stanford to both the Ashley lab and also a Stanford Catalyst group Motivating Mobility, as well as beyond Stanford through publications and conferences.
Graduate degrees that emphasize engineering, computer science and statistics are preferred.
Domain expertise with either mobile analytics, EMRs or wearable data would be ideal, though experience with some other “Big Data” (NGS/omics, MRI, etc) could be a suitable replacement.
You should be ready to harness a cluster – the sensor, device and CoreMotion data are large
Experience with Python and Linux bash scripting
Experience with experimental design protocols
Basic knowledge of code management such as git
Exposure to data analytics toolsets such as R, SciPy/NumPy
Required Application Materials:
Brief statement of interest
Contact information for three references
Send application materials to firstname.lastname@example.org with subject line “Postdoc”
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