Multi-Omics Approaches to Assessing Risk for Type 2 Diabetes & Responses to Risk Reduction Interventions
ABOUT THE PROJECT
Project Description
This program of research is focused on assessment of multiple levels of -omics data to apply machine learning approaches to identify novel biomarkers for type 2 diabetes risk and responses to risk reduction interventions.
Funding
Yes
LOOKING FOR
Required Skills
- R
- Git/Github
- MLlib / machine learning tools
Required Course Work or Level of Knowledge
- Statistics, intermediate
- Machine Learning, introductory
Acceptable Level of Education (eg. Undergrad, Grad Students, Post Docs, MD, PhD)
Undergraduate students, Graduate students, Postgraduates, Full-time workers who volunteer time
CONTACT
PI/Research group
Elena Flowers
Contact
Elena Flowers, [email protected]