Quantitative integration of big data to understand Earth-life history

Home / Student Life / Internships, Research and Professional Development / Research / Opportunities / Quantitative integration of big data to understand Earth-life history
Sponsoring College, Department, School or Center: 
SOLS
Faculty Name: 
Greer Dolby
Preferred Skills or Majors: 

A background in any STEM field is appropriate, but an emphasis on computational, programming, or mathematic skills (or enthusiasm to learn these) is desired, along with an ability to work independently. The successful student will enjoy problem-solving. Course credit, work study, or employment at ~10 hrs/wk are possible following a semester of productive work on the project.

Compensation: 
unpaid
Closing Date: 
September 15, 2019
Location or Campus: 
TEMPE
Hours Per Week: 
10

Desired Academic Year: 
Freshman
Sophomore
Junior
Senior
Project Description: 

The Dolby lab is looking for a highly motivated undergraduate to contribute to a new NSF-funded consortium aimed at understanding the external controls on biodiversity and genomic divergence through time. This position is a good fit for someone who is either: 1) interested in new ways of quantitatively converging big data from different disciplines, or 2) is interested in geobiology, particularly how to integrate geologic data with organismal genetic data. The position will integrate results from geophysical models with genetic simulations and the trainee will receive close mentorship on all aspects of the project, along with freedom to steer the project if they choose.



Application Instructions and Contact Info: 

Email Dr. Greer Dolby (gadolby@asu.edu) with a resume/cv that includes relevant courses/experience and a brief note about why this project interests you. Include the words ‘EF-ad’ in your subject heading. Informal inquiries are welcome.