Are you a highly motivated data scientist 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 post doctoral fellow 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 successful applicant will bring an expert level of working with real data on real problems to the position and understand the demands of conducting research in a fast-paced environment. This person must be professional, enjoy working in a high-volume environment with ability to multi-task, and be able to apply strong organizational and communication skills while being flexible in their daily routine. If this is you, we invite you to apply to become a member of our Lab.
In particular, you will have opportunities to join multiple interdisciplinary large database research projects relating to poeple at the Population Informatics Lab. Some examples are
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.
If you are interested in our research, please email Dr. Hye-Chung Kum directly: kum (at) tamu (dot) edu.