The Mathematical Sciences in Obesity Research
Dates: Monday July 31st to Friday August 4th
Format: In person at the IU School of Public Health-Bloomington campus.
Overview:
The mathematical sciences including engineering, statistics, computer science, physics, econometrics, and mathematics qua mathematics are increasingly being applied to advance our understanding of the causes, consequences, and alleviation of obesity. These applications go beyond routine approaches easily implemented in available commercial software. Rather, they increasingly involve computationally demanding tasks, development of novel measurement techniques and software, new quantitative derivations, and an exceptional degree of interdigitation of two or more existing techniques. Advances at the interface of the mathematical sciences and obesity research require bilateral training for investigators in both disciplines.
Objectives:
- To expose researchers from the mathematical sciences and obesity to the language and methodology at the interface of both disciplines,
- To facilitate collaborations between the two groups through effective contact, and
- To guide early investigators interested in conducting research at the interface of the mathematical sciences in obesity on the next career step.
Target audience:
Advanced graduate students, postdoctoral fellows, and early career scientists from quantitative and/or obesity disciplines. Persons of all genders, race/ethnicities, and ability/disability statuses are strongly encouraged to apply.
Applications for this course are now open! Priority consideration will be given to applications received by May 15, 2023. Applications will remain open until enrollment is filled. Click here to apply: Click here
Scholarships are available. To be considered for a scholarship, fill out the appropriate sections in the application form.
Contact:
For questions, please contact Cynthia Herrera Alley at cherrera@iu.edu.
Sponsor:
We thank our sponsor for their support: 
NIH Disclaimer:
This material is based upon work supported by the National Institutes of Health under Grant No. (R25DK099080). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Institutes of Health.