Summary

We are seeking a motivated, detail-oriented, and creative Research Associate to join a team of microbial genomics scientists at Baylor College of Medicine in the Department of Molecular Virology and Microbiology. The Tisza lab seeks to understand the genotype-phenotype relationship of human-associated viruses and bacteria through the lens of genomics. The Research Associate will conduct wet bench protocols and experiments as part of an effort sequence bacteria and viruses from wastewater as well as human-derived samples. This is an opportunity to develop new skills, gain mastery of the scientific method, and generate data that will provide insights to public health experts and genomics scientists. May also spend several hours per week developing bioinformatics skills under Dr. Tisza's guidance.

This role has the future potential of a hybrid work schedule with four onsite days per week.

Job Duties

• Developreusable, reproducible, performant, and distributable data analysis workflows
• Preparelibraries and conducts genomic sequencing on microbial DNA and RNA
• Maintainscrupulous electronic laboratory notebook and code repositories
• Meetregularly with the PI and team members to exchange knowledge and refine goals
• Maintaintheir physical and computational workspace and keeps lab inventory up to date
• Contributeto common lab tasks such as ordering and equipment maintenance
• Generatedetailed and “future proof” standard operating procedure documents for key lab protocols
• Generate figures and writing in advance of scientific publications
• Performother job related duties as assigned

Minimum Qualifications

• Master's degree in Basic Science or a related field.Experience in lieu of degree will not be accepted.
• Three years of relevant experience typically as a Research Assistant, Research Technician or Postdoctoral Fellow/Associate.

Preferred Qualifications

• Master's or doctoral degree in genomics, microbiology, or bioinformatics
• Experience with data analysis in R, python, or rust
• Experience with DNA sequencing machines
• Experience with Oxford Nanopore or PacBio sequencing machines
• Experience with genomic bioinformatics