and the USA BFF-AFIRMS, (Best Future Forest: advanced forest genomics and integrative resource management system), is a transformative initiative aimed at digitalizing forest resource management and tree improvement in Alberta, Canada. This is a joint effort across Government of Alberta, industry partners of Tree Improvement of Alberta, University of Alberta (CA), and Oklahoma State University (USA), aiming to integrate high-throughput genotyping, predictive analytics, and decision-making support to ensure responsible stewardship of forest genetic resources in the face of climate challenges, as well asincreasing demand for sustainable forest ecosystems and products. BFF-AFIRMS invites applications for full-time Quantitative/Statistical Geneticist postdoc/research associate positions to lead quantitative genetics and statistical modeling efforts within the project. The successful candidates will play a key role in leveraging existing genomic, phenotypic, and environmental data to dissect components of variance, estimate effective population size, identify genetic and environmental associations, and conduct genomic prediction and optimize selection and breeding designs. Qualifications: § Ph.D. degree in Statistics, Quantitative Genetics, Plant Breeding, or related field with a focus on associative analysis and genomic prediction. § Strong expertise in statistical modeling, quantitative genetics, genetic mapping, genomic selection, and association analysis. § Proficiency in programming languages such as Python and R for large-scale data analysis and modeling. § Experience with genotyping technologies, and population genomics in plant or tree species is highly desirable. § Familiarity with tree species or plant breeding programs is desirable, but not required. § Excellent analytical and communication skills, team collaboration abilities, and a passion for translating genomic knowledge into practical solutions for end-users. Benefit Highlights: § Competitive compensation- full time employment with competitive compensation scale at federal agencies such as NSF in the USA and NSERC in Canada. § Dynamic work environment- be part of a highly dynamic multiple-disciplinary team environment across academia, government, and industry partnerships. § Flexible work arrangement- benefit from flexibility with hybrid work (on-site and work from home) arrangements after the initial employment process. How to Apply and Required Documents § A cover letter addressing research interest, experience and skills that fulfill the requirements. § A full C.V with most recent or most significant publications. § Contact information for 3 potential referees. Candidates should prepare the documents as ONE PDF FILE and subm
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