Postdoc position in Applied Quantitative Genetics of Livestock at University of Alberta
Several positions are available immediately at the Department of Agricultural, Food and Nutritional Science, University of Alberta. Successful applicants will join a very successful team of researchers at the Livestock Gentec Center to develop and implement genomic tools to improve feed efficiency and other economically relevant traits in beef cattle. Major research responsibilities include: (1). Development and implementation of methodology for genetic evaluation of breeding stock for multiple traits; (2). Development and implementation of methodology to incorporate genomic information into genetic evaluation to improve accuracy; (3). Development and implementation of genomic prediction equations to predict genetic merit of complex traits for breeding stock; (4). Development and implementation of multiple trait selection indexes to assist with breeding programs. (5). Assist with development and maintenance of large databases.
Applications must have a Ph.D degree from a recognized university in areas of Quantitative Genetics and/or Statistical Genomics. Candidates must have a good understanding of theoretical and computational principles related to the analyses of quantitative and molecular data for the purpose of genetic evaluation and genomic prediction. The candidates must also demonstrate skills and working experience in computer programming preferably in C, C++, ASreml, SAS, R or Perl to develop customized programs for genetic evaluation and genomic prediction. The ability to effectively communicate and collaborate with colleagues in research and extension is essential. Previous research experience in cattle is desirable. Knowledge and experience working with large databases will be an asset.
The initial appointment will be for one year and is renewable upon satisfactory performance. The salary is commensurate with experience. Interested candidates should submit full curriculum vitae, a statement of qualifications and experience, and names of three referees to:
Dr. Graham Plastow
Professor and CEO, Livestock Gentec Center
Department of Department of Agricultural, Food and Nutritional Science
University of Alberta
1400 College Plaza
8215-112 Street, Edmonton, Alberta, Canada T6G 2C8
Phone: 780-492-1496; Fax: 780-248-1900
MSc Graduate Research Position for a project on “The use of genomics for the genetic improvement of the Hays Converter”.
The Hays Converter (HC) is a beef breed developed in Canada in the 1950s. Initial work used pedigree records to determine genetic diversity and levels of inbreeding of the breed. A positive rate of inbreeding and a decrease in the amount of genetic diversity was found. Single trait and bivariate animal models were used to determine genetic parameters and trends for growth, ultrasound, and carcass traits. An increasing genetic trend was found for growth traits which the breed was selected for. All of the animals in the herd along with some ancestors have been genotyped. The accuracy of imputation from 6k to 50k marker panels using a reference group of 100 animals was determined. Imputation was performed with a high accuracy (>0.93) for pure Hays Converter animals, but was found to be unsuccessful when individuals had large contributions from additional breeds. This work forms the foundation for future management and improvement of the breed. This new project will seek to develop new tools for improving the breed including the development and application of selection indexes, the use of genomic pedigree matrix for control of inbreeding and mate allocation, and the further investigation of the genetic architecture of the breed and its use to model GWAS and genomic selection across HC and other populations.
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Graduate Student Position Details
cow/calf performance in the Mixedgrass Prairie of southern Alberta. This investigation is unique in that it will combine the disciplines of genetics, animal science and rangeland management to field test RFI in native grasslands. In addition, variation in animal performance (production metrics and efficiency) will be further explored by evaluating animal-based differences in habitat selection, forage use and grazing behavior across the landscape.
Applicants should have a background in animal science, range or pasture management, environmental sciences, or a related field.
A valid class 5 (non-probationary) drivers license is required.