Join Us

Population Informatics Lab: We have multiple open positions

Are you a highly motivated data scientist (or want to be) looking for a chance to get involved with exciting research in the emerging field of population informatics? Do you learn by actually working on real problems? Would you like to apply your data science skill to work on real problems with real data about people and become an expert SAS programmer (prior knowledge not required, but desire to learn required. This is one of the man languages used to manipulate health data)?

The Population Informatics Lab, under the lead of Dr. Hye-Chung Kum (cross trained in computer science, PhD in dataminig, and masters in policy & management), is now accepting applications for talented postdoctorol, graduate and undergraduate students in computer science and health service research (and related fields) to work in the area of Data Science with health, behaviour, and population data. In particular, you will have opportunities to join multiple interdisciplinary large database research projects relating to poeple at the Population Informatics Lab.

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

Post-Doctoral/Graduate Research Fellow in Ethics, Law, Data Science, and Artificial Intelligence

Population Informatics Lab and Program in Health, Law, and Policy

We are looking for a recent graduate of a J.D. (law) or Ph.D. (bioethics, ethics of technology, or related field) program. In this role, the research fellow would join an interdisciplinary team exploring legal or ethical issues relating to the use of data in a variety of contexts, including database studies, commercial big data, public health surveillance, law-enforcement surveillance, artificial intelligence etc.  Ideal candidates would have a strong background in law or ethics and a capable comprehension of data science and related technologies. Skills or experience in legal epidemiology would be a bonus but not required. This position will include writing reports, papers, and proposals, so strong writing ability is highly desired.

Interested candidates should reach out to Cason Schmit, JD, at schmit@tamu.edu


Post Doctoral Fellow in Data Science and Population Informatics

We are recruiting for post doctoral fellows in data science to join the Texas A&M Institute of Data Science (TAMIDS) and the Department of Health Policy & Management, School of Public Health, Texas A&M University, College Station, TX. The starting dates are flexible (available starting now). Applications will be considered until the positions are filled. The position is multi year with competitive salary.

Qualifications

If this is you, we invite you to apply to become a member of our Lab.

Job Description

If selected, you will be one of the TAMIDS Postdoctoral Fellows and join a peer group of data scientists at TAMIDS collaborating on interdisciplinary data intensive research.

Some examples are


How to apply

If you are interested in our research, please email Dr. Hye-Chung Kum directly: kum (at) tamu (dot) edu.


TAMU Graduate & Undergraduate Students in Computer Science

If you are interested in joining the lab, email Dr. Kum the following. We will be receiving applications until the positions are filled.


Who are we

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 UNC-CH and Texas A&M.  Dr. Kum, the lead, is a data scientist with training in both computer science and Health and has worked with many data scientists, computer science students to do research on health informatics problems. For more information poke around other sections of this website.

Texas A&M Institute of Data Science (TAMIDS) pursues new approaches to Data Science research, education, operations and partnership. These approaches cross college boundaries to connect elements of Data Science from engineering, technology, science and the humanities, and inform wider social challenges.