Job Description - Computational Genomics Analyst, Department of Entomology and Plant Pathology (UTIA) (24000001DI)
The Department of Entomology and Plant Pathology, University of Tennessee Institute of Agriculture is seeking to fill a Computational Genomics Analyst position as part of our growing bioinformatics team. The Computational Genomics Analyst will work in advancing genomics and bioinformatics research at the University of Tennessee, Knoxville. The analyst will provide bioinformatics support to UT investigators driving innovation in genomics and transcriptomics research projects. The candidate will provide bioinformatic and computational consultation and expertise to support student, staff, and faculty researchers, performing bioinformatics analysis to a broad base of research needs (genome assembly, functional/structural annotation, variant calling, population genetics, transcriptomics, etc.). In addition, the candidate will provide custom analysis, contributing to the development of bioinformatics pipelines, and management of large-scale genomic data sets across multiple biocomputing resources. While this position is support oriented, the candidate will also have opportunities to engage in collaborative and independent research and to participate in and lead peer-reviewed publications.
Key Responsibilities
- Collaborate and communicate with researchers to design and execute bioinformatics analyses to address specific research questions utilizing software to perform standard bioinformatic analyses using short and long-read sequencing technologies.
- Work closely with investigators to facilitate, manage, and document all steps of data analysis over multiple research projects. Commitment to providing service while communicating with researchers from diverse backgrounds, as well as the ability to work independently are critical competencies for the role.
- Design and carry out custom bioinformatics projects for researchers involving more sophisticated protocols as well as custom tools and pipelines as needed.
- Track and report on projects including reproducible documentation of analytical methods for all projects.
- Work with LINUX servers and local HPC resources and routinely perform software installation and large data management.
- Contribute to manuscript and proposal preparation.
- Guide and train graduate students and staff in bioinformatic analyses, software use, and data management.
- Develop and deliver short courses online and in person with conceptual and practical data analysis components.
Requirements
- MS in Bioinformatics or other computer science.
- One year of related experience in contemporary genomic/transcriptomic data analysis; a Linux HPC environment; or statistical analysis.
- Independently prioritize tasks, ensuring timely completion of project goals while maintaining high-quality standards.
- Programming fluency with at least one general-purpose programming language (e.g., Python, Perl, C/C++) and one language for scientific computing (R, MATLAB, Python).
- Strong written and verbal communication skills.
- Competence facilitating interaction and communication with others.
Preferred Qualifications
- PhD in Bioinformatics or other computer science.
- Two years of related experience in at least two of the following areas: genome assembly; structural annotation / functional annotation; variant calling, association/linkage analysis; population genetics / phylogenetic analysis; differential expression (enrichment analysis/network analysis); using version control (Git, GitHub, etc.); working with plant, insect, and/or fungal pathogen systems.
Position Classification: Researcher 1, Exempt, MR 08, Regular Full Time.
For Specific Questions, contact committee chair Dr. Meg Staton at mstaton1@utk.edu
Schedule: Full-time
Job Posting Date: Jul 3, 2024, 12:04:13 PM
EEO/AA Statement / Non-Discrimination Statement: The University of Tennessee is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA institution in the provision of its education and employment programs and services. All qualified applicants will receive equal consideration for employment without regard to, and will not be discriminated against on the basis of, race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, or covered veteran status.
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