Graduate Research Fellow--Predoctoral Training in Biomedical Big Data Science 2018
Department of Statistics and Data Sciences - College of Natural Sciences - The University of Texas at Austin
Location: Austin, TX
Open: Sep 20, 2017 • Close: Mar 31, 2018
The NIH BD2K T32 pre-doctoral training program at UT-Austin
The ever-increasing accumulation of data continues to outstrip the graduate training needed to meaningfully mine the data collected. This issue is further complicated by the fact that holistic training in biomedical big data analysis requires PhD-level expertise in not one, but three core research areas: (1) biology (2) statistics and (3) computer science, yet the majority of traditional PhD training programs demand that students choose just one of these areas as their focus. A growing number of biomedical PhD students are recognizing the need to develop data analysis and computational biology skills, at the same time that a growing number of computer science and statistics PhD students are realizing that their marketability could be substantially expanded if they knew how to apply their skills to solve outstanding problems in the health arena. The purpose of this pre-doctoral training program at The University of Texas at Austin is for the trainee to become an expert in one of the following areas: 1. Statistics (STAT); 2. Computer Science (CS); 3. Computational science, engineering, and mathematics (CSEM); or 4. Biology (via a PhD in one of a. neuroscience [NS]; b. ecology, evolution, and behavior [EEB]; c. cell and molecular biology [CMB]; or d. Biomedical Engineering [BME]) while also obtaining essential training in all three core areas (statistics, computer science, and biology).
Training for the program involves three formal components:
- core courses (3);
- research lab rotations (2);
- seminar/workshops course.
Benefits of the program include: two years of prestigious fellowship funding; training in statistics, computer science, and biology via three formal courses, a seminar course, and research rotations, funding for travel to NIH BD2K consortium meeting in Bethesda and to a national Big Data science meeting (while supported by training grant); excellent and enhanced job prospects upon graduation.
UT-Austin PhD student in Statistics, Computer Science, Biology (via Neuroscience, Ecology, Evolution & Behavior, Cellular & Molecular Biology, or Biomedical Engineering) or Computational Science, Engineering & Mathematics (CSEM).
These positions are open to permanent residents and US citizens only. Women and minority students are encouraged to apply.
Applicants must be enrolled in one of the participating graduate programs and should be either beginning their first or second year of graduate study as of Fall 2018.
Applications will consist of these items: Interfolio application, CV, current graduate transcript, unofficial copies of undergraduate transcripts, list of current courses, one letter of support from a UT-Austin faculty member, and a one-page statement of interest.
Application deadline is February 28, 2018.
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.