Research Associate

Research Associate 

The Ji Lab at the University of Texas at Tyler (UTT) focuses on regenerative niches for the remodeling of injured lungs. UTT North Campus is widely recognized for its exceptional, innovative, and collaborative research environment, and is investing significant resources in expanding interdisciplinary research in the computational, genomic, cellular, and molecular bases of pulmonary diseases. The Ji Lab is dedicated to applying state-of-the-art computational strategies to identify new molecular endotypes, biomarkers, and microbiota of acute lung injury/acute respiratory distress syndrome (ARDS). The lab is located in the UTT North Campus, a heavily shaded campus by southern pine trees, and on I-20 in east Texas.

Job Description

This position is available immediately at the Ji Lab. The individual will identify and implement computational solutions to research problems related to ARDS and sarcoidosis. They will be responsible for taking on highly interdisciplinary projects and key functions in this endeavor, including applying state-of-the-art open-source software for basic and advanced analysis of next-generation sequencing data (scRNAseq) and proteomics data. They will also analyze epigenetics and transcriptomic datasets.

The ideal candidate will be highly motivated, well organized, manage time effectively, and can work independently as well as part of a team. They will have a background in bioinformatics, computational biology, and/or biostatistics and have essential skills of biological lab.

Job Duties

• Analyze omics data using online available R or Python packages for omic data processing.
• Process omics data for clustering and function annotations to identify new endotypes.
• Identify biomarkers from human and microbial proteins using R or Python.
• Correlate identified molecular endotypes with phenotypes
• Collaborate with wet lab scientists to prepare cell/tissue samples for LC-MS and scRNAseq
• Prepare reports, charts, and graphs for presentations and publications
• Maintain detailed records of computational code and processes
• Manage omics and metadata
• Search and evaluate scientific literature in support of research projects
• Prepare manuscripts, progress reports, and grant applications.

  Preferred Qualifications

  • Programming Languages: Python, R, and others Analytical: critical thinking, data modeling, problem-solving, troubleshooting Demonstrated ability working with open-source bioinformatics software Experience in bioinformatics analysis of RNA-Seq and proteomics data A record of taking initiative to solve problems and working to high-quality standards Attention to detail and accurate record keeping Ability to multitask, work and learn independently, and be self-motivated Publication record: demonstration of productivity in omics data analysis Masters’ or Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Genetics, Biology or a related field. Multi-disciplinary trainee, with a working experience of 3+ years, is preferred.

  To Apply

  Please email a cover letter explaining relevant work experience, a CV, and the names and contact information for three references to hji@uttyler.edu. A short list of candidates will be directly contacted by the PI.

  Additional Information

  As an Equal Opportunity Employer, the University will, in accordance with State and Federal law and regulations, provide equal opportunity in all employment related activities without regard to race, color, religion, national origin, gender, age, disability, sexual preference, or status as a disabled veteran or a veteran of the Vietnam Era.  The University requires pre-employment drug & alcohol screening, proof of COVID-19 vaccination and/or medical or religious exemption, and health immunizations and criminal background check on all hires. Specific job requirements or physical location of some positions allocated to this classification, may render this position security sensitive, and thereby subject to the provisions of Section 51.215, Texas Education Code