18 days old

Data Science Fellow at Stanford University School of Medicine

Stanford University
Stanford, California 94305
  • Job Type
    Employee
  • Job Status
    Full Time

About us: We are a group of about twenty doctors, engineers, informatics professionals and students focused on enabling better care using existing health data. We develop novel methods to learn from patient-level health data including structured health encounter records, clinical notes, insurance claims, diagnostic imaging, and clinical trial data. A major research thrust is to answer clinical questions that enable better medical decisions using electronic health records (EHRs) and insurance claims data, via a consultation service that uses aggregate patient data at the point of care (https://shahlab.stanford.edu/greenbutton). We also have an active research program to research safe, ethical, and cost-effective strategies for predictive models to guide mitigating care actions (https://shahlab.stanford.edu/paihc). Our research group is part of the Department of Medicine at Stanford.

About the position: The primary research focus of this postdoctoral scholar position is flexible, and will involve developing and advancing methods for data-driven bedside decision making, or machine learning for health system-level improvements. An additional operational focus will involve being responsible for our group’s data analysis and compute infrastructure, including managing dataset ingestion and cleaning, database management, and supporting the cloud compute needs of our lab members. The position offers the opportunity to work with leading Stanford faculty in Informatics, Statistics, and Medicine as well as an opportunity to build real-world credibility in DataOps.

About you: You are a hands-on team member with research experience who collaborates with medical doctors, statisticians and computer scientists to advance methods for clinical decision making using observational health data and/or improving patient care via machine learning. You will manage our data and compute infrastructure to turbo-charge the research of our entire team. You are a contributor at all levels: designing methods as well as experiments to evaluate them, implementing robust code, and coordinating with our collaborators.

You will find this position to be a good fit if you:

  • are passionate about improving health care
  • can set up a GCP instance in your sleep
  • are excited to work with rich, sometimes messy, patient-level data
  • thrive in dynamic, fast-paced environments

You look forward to responsibilities that include:

  • developing and evaluating informatics methods to derive actionable findings from healthcare data of millions of patients
  • pushing the limits on what relational databases can handle
  • healthcare data wrangling including dataset cleaning and access infrastructure
  • producing scalable, reusable code
  • writing manuscripts and progress reports about your research
  • working in a team of researchers

Requirements

You meet all of the following requirements:

  • PhD in CS, medical informatics, bioinformatics or related quantitative discipline
  • experience in processing and analyzing large datasets
  • 3+ years database management experience
  • 3+ years of coding experience
  • fluency in linux system administration
  • excellent written and oral communication in English, with at least one peer-reviewed first-author manuscript

You meet some of the desired qualifications:

  • 1+ years of experience analyzing health data, such as insurance claims and EHRs
  • knowledge of best practices in data mining and machine learning
  • app and/or Web development
  • GCP system administration

Categories

Posted: 2020-07-22 Expires: 2020-08-21

Before you go...

Our free job seeker tools include alerts for new jobs, saving your favorites, optimized job matching, and more! Just enter your email below.

Share this job:

Data Science Fellow at Stanford University School of Medicine

Stanford University
Stanford, California 94305

Join us to start saving your Favorite Jobs!

Sign In Create Account
Powered ByCareerCast