The Population Informatics Lab, under the lead of Dr. Hye-Chung Kum (cross trained in computer science, PhD in datamining, and masters in policy & management), is now accepting applications for talented young data scientist/computer scientist. The job will entail working on all aspects of the full data life cycle with large datasets (e.g., claims data, telemonitoring data) to answer real world questions (e.g., impact of COVID-19 on emergency department visits; trends on cancer screening and survival rates; predicting hypertension risk scores) on population health. The full data life cycle include, planning, data governance, data ingest, data engineering, data analysis, building/training models (e.g., machine learning, AI), data visualization, result dissemination (e.g. presentations, publications), and computing infrastructure support. Young data scientist/computer scientist will get on the job training and experience to build skills on the full data pipeline.

This is a full time job with full benefits. Onsite in College Station. Minimum 1 year commitment, 2 years preferred contingent on performance. Programming experience required in some language. 

Apply by emailing kum (at) tamu (dot) edu: See details below

If you are interested in joining the lab, email kum (at) tamu (dot) edu the following. We will be receiving applications until the positions are filled.

• CV

• IMPORTANT: How did you learn about this job? (e.g., who referred you). 

• List your proficiencies in programming languages (e.g., R intermediate; SAS beginner) 

• A short description of why you are interested in joining this lab

• Your midterm and long term career goals

• Your preferred start date

• Transcript (unofficial is ok)

• Your major GPA

The Population Informatics Lab applies informatics, data science, and computational methods to the increasingly large digital traces available to advance public health, social science, and population research. This research group is a joint effort between School of Public Health and TEES at Texas A&M University.  Dr. Kum, the lead, is a data scientist with training in both computer science and Health and has worked with many data scientists, computer scientists to do research on health informatics problems. For more information poke around other sections of this website.