Understanding the Basis of Diabetes and Diabetic Complications using ‘Big Data’

Mentor Name:
Marcus Pezzolesi

Mentor Position:
Associate Professor

Internal Medicine



Project Description:

The primary focus of the Pezzolesi lab is to understand the etiology of diabetes and diabetic complications using high-throughput next-generation sequencing technology and integrated ‘big data’ and ‘omics’-based approaches. The lab leverages large data resources combined with next-generation sequencing to perform gene discovery in families enriched for diabetes and diabetic kidney disease. Several research opportunities (both computational and wet-bench) exist for highly motivated students!

Opportunity Type:

Volunteer; This is a paid research position; This is a work-study research position; Prepare a UROP proposal; Write an Honors Thesis or Senior Thesis; Earn independent study credit

Student Role:

Students will have opportunities to gain first-hand research experience in the generation, analysis, and interpretation of genetic and/or other 'omics' data.

Student Benefits:

Students will gain research experience and contribute to publications with co-authorship. Potential volunteer, work study, paid, research for credit opportunities exist.

Project Duration:

It is expected that students spend 10 hours per week on the project during the academic year. Potential full time summer employment opportunities may exist.

Minimum Requirements:

Motivation and enthusiasm for research. Coursework could include biology, genetics, biochemistry, mathematics, and bioinformatics. Training will be provided.