The Animal Quantitative Genetics group at Michigan State University is seeking a research associate, postdoctoral researcher, to work on characterization of allelic and haplotypic variation in Holstein cattle using very large datasets (sequence, RNAseq and genotypes).
The successful candidate will work on assembly, phasing and imputation of large datasets up to sequence level; variant calling, haplotype identification and functional annotation. The position will also develop and test efficient methods to evaluate accuracy and validate results. The work also includes genomic prediction with haplotypes, identification of putative causal variants and testing their value for prediction purposes. The emphasis of the project is on dairy cattle, but method developed should be extensible to other species as well.
The specific duties of this position include:
Independently plan and conduct analyses of very large genomic datasets.
Publish research outcomes in peer-reviewed articles in high impact journals.
Discuss and communicate research ideas with colleagues and industry.
Develop methods and computer programs to perform the analyses.
Undertake data analysis and other modeling exercises relevant to the project
Assist with supervision of graduate students
This position is initially for one year renewable annually contingent on performance and availability of funding. The starting date is flexible but preferably before March 2019. Review of applications will start immediately, and the position will remain open until a suitable candidate has been found. Salary is commensurate with experience plus benefits.
Doctorate -bioinformatics, animal genetics or a rel
Appropriate qualifications and research training relevant to the duties, including completion of a PhD degree in bioinformatics, animal genetics or a related area and some academic work experience.
In depth knowledge of high-throughput genomic technologies and relevant analytical tools
Extensive experience with genomic datasets, particularly assembly, variant calling, phasing, imputation and functional analyses.
Experience in computer programming, particularly R and C++, with the ability to communicate with databases and to handle extremely large data files.
A strong record of research achievement as demonstrated by journal publications.
Strong communication skills with the ability to liaise with industry.
High level understanding of quantitative genetics and its role in animal breeding programs.
Required Application Materials
Cover letter summarizing your background relevant experience
Most recent CV
Contact information for three referees
Review of Applications Begins On
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Internal Number: 553277
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