Postdoctoral Fellow - Computational Genetics

International Rice Research Institute(IRRI), Laguna, Philippines

Skill Required:, Research and Analysis
Preferred Experience: 
3 to 10 Years
Closing Date for Applications: 
3rd March, 2015

Job Description

Job Purpose

  • The successful candidate will lead efforts to apply next-gen sequencing and high-density SNP (single nucleotide polymorphism) genotyping on a large-scale across breeding populations to help accelerate the rate of genetic gain for IRRI’s irrigated rice breeding programs. This position will coordinate across breeding, quantitative genetics, marker applications, breeding information management, and bioinformatics groups to integrate the latest genome-wide selection strategies into existing breeding programs, in combination with targeted selection of major genes and QTLs (quantitative trait loci), as part of a larger effort to transform IRRI’s rice breeding programs into highly-efficient, modernized, industrial-scale variety development pipelines.
  • This position is based in IRRI Headquarters, Los Baños, Laguna, Philippines.

Roles and Responsibilities

  • Lead efforts to apply computational genetics methods and bioinformatics tools on large NGS (next-generation sequencing) and SNP datasets of breeding populations as the basis for selection using genomic-estimated breeding values, in coordination with IRRI’s Genotyping Services Lab and the bioinformatics and quantitative genetics teams.
  • Analyze NGS and SNP data to characterize SNP haplotype patterns and define alleles and donor introgressions for major genes of interest in breeding materials and improve the predictive ability of trait-specific markers, in coordination with IRRI’s bioinformatics, trait development, and marker validation teams.
  • Help optimize the molecular marker analysis workflow at IRRI to enable rapid processing of high-throughput genotyping data of breeding materials using an integrated LIMS and data management pipeline, working closely with the bioinformatics and breeding information management teams.
  • Assist in the effort to validate predicted marker-trait associations from ongoing GWAS (genome-wide association study) projects and quickly introgress high value GWAS hits and QTLs into the breeding populations.
  • Report results through publications in international scientific journals, project reports, and conferences.


  • PhD in Computational/Statistical/Quantitative Genetics, Bioinformatics, Computer Science, Plant Genetics, or closely related field;
  • Experience in the application of molecular markers in the genetic analysis of populations, demonstrated success in using bioinformatics tools in the analysis of high-throughput genotyping and sequencing data sets, and a working knowledge of plant genetics.

Skills Required

  • Experience with genomic selection;
  • A familiarity with high performance computing systems with diverse operating systems, and programming skills using statistical, scripting, database, and software development languages(R, Perl, Python, SQL, and Java)are preferred;
  • Fluent in written and oral English.

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