Quantitative Genetics/Genomics Data AnalystDepartment:
Animal Science-0830Requisition Number:
F_200138Posting Open Date:
03/15/2021Application Review Date: (To ensure consideration, please submit all application materials before review date):
05/17/2021Open Until Filled:
NoDescription of Work:
The purpose of this position is to support multi-disciplinary research using genetic/genomic data to answer animal biology and animal management questions. This position will support the analysis of phenotypic, pedigree, and genomic data in beef cattle for a wide-range of animal science disciplines including physiology, ruminant nutrition, meat science, breeding and genetics, and microbiology.
Duties will be oriented toward analysis of pedigree, phenotypic, and high-density genomic data in beef cattle. Specific responsibilities include, but are not limited to:
1)Genome-wide association studies of a wide-array of trait complexes.
2)Genetic parameter estimation.
4)Quantitative validation of genomic-based predictions and identified variants.
5)Development of data editing and analysis scripts and pipelines.
6)Maintenance of software and servers.
7) Contributing to publishing of research results.
Expected to work under the guidance of the supervisor to accomplish the research goals, prepare manuscripts for publication and prepare competitive grant proposals. Oversight for the position will be provided by Dr. Matthew Spangler (Animal Science).
A non-tenure leading research faculty position may be appointed annually for a maximum of five years. Continuation of the position from year to year will depend on satisfactory performance and availability of funding.
As an EO/AA employer, qualified applicants are considered for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See http://www.unl.edu/equity/noticenondiscrimination.Minimum Required Qualifications:
Ph.D. in animal breeding, statistical genetics/genomics or a related field.Preferred Qualifications:
Preferred skills include a solid background in quantitative genetics, biostatistics, bioinformatics, programming (e.g., R, python, Fortran, and/or C/C++), use of common software for analysis of genetics data, analysis of non-normally distributed data, and large-scale dataset analysis.Criminal History Background Check Required:
YesHow to Apply:
Click “Apply to this job” and complete the information form. Attach 1) a cover letter that describes your qualifications for the job, anticipated contributions, and your experience 2) your curriculum vitae; and 3) contact information for three professional references (or arrange to have reference letters sent to [email protected]).For questions or accommodations related to this position contact:
Matt SpanglerJob Category (old):
mspangler [email protected]
Faculty Non-Tenure LeadingJob Type:
12 Month (Faculty Only)Position funded by grant or other form of temporary funding?: