Job Description

Major/Essential Functions

Conducts large-scale genomic data analysis, including RNA-Seq, scRNA-Seq, and ChIP-Seq. Conducts statistical and bioinformatics analysis. Data visualization (prepares graphs, tables and other materials for publications and presentations). Writes manuscripts.
Trains lab personnel and students to perform data analysis (including large-scale) and helps with ongoing projects that require data analysis
Maintains appropriate documentation related to analyses (lab notebook and/or electronic notes) and software/ bioinformatic tools inventory
Verifies the good working order of all computational equipment, including NAS and backup drives, daily, and takes immediate measures when malfunctions are noted.
Assists with molecular and cell biology assays, including cell and nuclei isolation, isolation of RNA and DNA, and qPCR. Assists with behavioral techniques in mice.
Other tasks as assigned.

Occasional Duties

Other misc assigned task by supervisor

Required Qualifications

Bachelor's degree in one of the sciences, or equivalent combination (four (4) years) of job-related experience and college education. Experience may be substituted for college education on a year for year basis.

Preferred Qualifications

A bachelor's degree in biology, mathematics, computer science/ engineering, data science or related fields. General experience with tools and techniques in computational biology, including bioinformatics and working with large-scale biological datasets.
General experience with conducting research in a biological field.
Experience preferred: Analyzing large-scale genomic, transcriptomic and epigenomic data, such as RNA-Seq, scRNA-Seq and ChIP-Seq, multivariate statistical analysis, bioinformatics and data visualization. ·
Working knowledge of Linux/MacOS command line (file management and automation; system monitoring and troubleshooting); R & Python (data wrangling and visualization); cloud/high-performance computing(cluster management, e.g., Slurm and parallel computing); Interactive data analysis and documentation (e.g., Jupiter notebooks and code annotation); Version control; Pipeline development and testing. ·
Knowledge: Conceptual understanding of RNA-Seq technologies; familiarity with scientific equipment; working with advanced instrumentation attained through education or prior work experience.