The Microbial Ecosystems Lab (mSys) at Colorado State University is searching for 1 computational researcher to join our team. This researcher will work independently and contribute as a member to our dynamic, collaborative multi-disciplinary team of microbiologists, biochemists, computational biologists, and environmental scientists. We are looking for a new team member for projects related to performing microbial genomics research using computational and statistical analyses to decipher biological meaning from genome sequences and related data, including both DNA and RNA sequences, as well as other microbiome data. We are interested in team members who can contribute to projects working with PI Dr. Kelly Wrighton in the human gut, wetland soils, or agricultural systems (soils, rumen). Metabolism at various scales, from biochemistry, to microorganisms, to communities is a central focus of our research team.
Required Job Qualifications
- B.S. in bioinformatics, computational biology, statistics, computer science, or closely related field + 3 years related experience or a Master’s or PhD degree in computational biology, bioinformatics, or similar field or equivalent field
- A strong background in working with genomic and gene expression data including NGS analyses (mapping, variant calling, etc.)
- Proficiency in Python, adept at developing software and scripts for genome-enabled bioinformatics analyses
- Experience using Linux command-line tools and relational databases (SQL).
- Proven ability in software development, including best practices in testing, version control using git and continuous integration
- Excellent written communication skills, including the capacity to work independently to author software with clearly established protocols, and including coding best practices and reproducible research
- Ability and desire to communicate in cross functional teams with members from varying backgrounds
Preferred Job Qualifications
- Demonstrated experience applying genome analyses to microbial systems, especially working with multi-omic data
- Experience with multivariate statistics in a scientific programming environment like R, with a focus on microbial ecology analyses
- Background education or training in molecular biology, biochemistry, or microbiology
- Experience with developing web-based front-end interfaces is preferred
- Strong quantitative background (machine learning, Bayesian inference, etc.)
- Experience with workflow management tools (Snakemake, nextflow, etc.)
- System administration experience
All job details and application instructions can be found here https://jobs.colostate.edu/postings/115445