A Fall 2018 internship is available in the Eaton lab to work on the development and application of machine learning approaches to historical evolutionary inference. Research will involve learning to use high performance distributed computing infrastructure, performing population genetic simulations, fitting machine learning models, and writing reproducible shareable code. The ideal candidate will have experience and interest in Python coding and a reasonable understanding of linear algebra.

A mentoring plan will be developed with Professor Eaton to establish a time line for completion of the project by the end of the internship. Work in our lab is collaborative and encourages open science.

Faculty Advisor

  • Professor Deren Eaton.
  • Department/School: Ecology, Evolution, and Environmental Biology/A&S.
  • Location: Schermerhorn Ext. 1007

Project timeline

This is NOT a summer 2018 internship. It is for Fall 2018.

  • Start date: 09/01/2018
  • End date: 12/31/2018
  • Number of hours per week of research expected: 10

Candidate requirements

  • Skill sets: Python
  • Student eligibility (as of Spring 2018): freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Other comments: ideal candidate should have an interest in evolutionary genomics.