The Landweber Lab is looking for a computational student to work with us to analyze long-read DNA sequence datasets from Oxford Nanopore and PacBio (so-called third generation sequencing platforms). These datasets were collected across a time-course while single cells of the genus Oxytricha are undergoing RNA-guided natural genome editing. This process leads to a completely different “output” product genome from the precursor “input” or germline genome, and has been compared to a cellular computer. The goal will be to capture and classify long reads in these DNA datasets that represent the intermediate steps in genome rearrangements, when chromosomes mix and match hundreds of thousands of precursor building blocks to assemble a mature genome of 18,000 new chromosomes during programmed nuclear development.

Selected candidate(s) can receive a stipend directly from the faculty advisor. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Laura Landweber
  • Center/Lab: Landweber Lab
  • Location: Hammer Health Sciences Building, 701 W 168th St
  • The Landweber lab studies novel genetic systems in microbial eukaryotes, with a focus on RNA-guided natural genome editing and rearrangement in the unicellular model organism, Oxytricha.

Project Timeline

  • Earliest starting date: 9/20/21
  • End date: 8/12/22
  • Number of hours per week of research expected during Fall 2021: ~8
  • Number of hours per week of research expected during Summer 2022: ~35

Candidate requirements

  • Skill sets: Proficiency in any programming language, Python and Linux experience preferred. Bioinformatics training or course experience preferred and some knowledge of genomics
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes