Biomedical Data-Driven Discovery Training
The Biomedical Data Driven Discovery (BD3) Training Program at Northwestern University brings together Big Data educators and scientists from the Feinberg School of Medicine, the McCormick School of Engineering and Applied Science, the Weinberg College of Arts and Sciences and the School of Communication. Its goal is to train future scientists who will go on to develop novel Big Data methods that will advance science and improve health.
The submission period is April 1 to April 30, 2020.
Note: This T32 training grant provides one year of stipend, tuition, and meeting travel to successful candidates, as well as access to data science courses that are part of the Master of Science in Analytics led by Dr. Diego Klabjan. Three candidates will be selected.
Please direct questions about the program to Lucia Ontiveros at (312) 503-6585.
Applicants are considered based on:
- Status in a doctoral program, typically at the end of their first year (though other years may be considered)
- Applicants can be from either the Chicago or Evanston Campus of Northwestern.
- Strength of the study plan and its potential for success and impact on field
- A biomedical Big Data focus for the student’s planned dissertation research
- Evidence of the student’s commitment to a career in research
- Commitment to completing the BD3 curriculum and a doctoral degree
- Performance during the first year of doctoral training
- Status as a U.S. citizen or permanent resident
To be considered, complete an application in NITRO Competitions. You will need to provide:
- A study/personal statement (one to two pages) explaining what attracts you to Big Data/bioinformatics, your career goals, scientific interests and how you see your participation in the program enabling you to reach your goals.
- A one to two paragraph description of a potential research project, with input from the student's planned dissertation advisor. If the student has selected a dissertation topic, this should be described, otherwise a topic in the general area can be described.
- Contact information for the student's research advisor, who will submit a letter of recommendation.
- Most recent transcript
- A current CV