The Wheat Genetic Resource Center (WGRC) in the department of Plant Pathology at Kansas State University is seeking a Computational Biologist or Bioinformatics Scientist. The successful candidate will join a vibrant team of researchers investigating diverse aspects of wheat genetics and genomics focusing on the development of resources, tools, and strategies to identify and deploy beneficial wild relative diversity in breeding. The WGRC team uses a rich collection of wild relative germplasm, and a modern arsenal of genetics and genomics tools and resources combined with high-throughput phenotyping technologies to prioritize close and distant relatives of wheat for introgression into adapted varieties and assess their value for improving agronomic traits. This position’s focus will be on the computational analyses of large-scale phenomic and genomic data to investigate connections between wild-relative genomic variation and plant-level phenotypes. The successful candidate will identify valuable alleles and genes predictive of adaption to biotic and abiotic stress factors and variation in wheat productivity and end-use quality traits and will help prioritize genomic variation for incorporation into the wheat pre-breeding and breeding pipelines.
A successful candidate should have graduate level training in the fields of bioinformatics, quantitative genetics, or genetics, and will:
- Analyze large-scale datasets including whole genome sequences, RNA-seq profiling, genome-wide sequence variation, metabolomics and phenotyping datasets.
- Collaborate with research team members on projects aimed at prioritizing genomic variants for breeding and genome engineering.
- Lead the development of genomic databases, and their integration with public genomic resources to facilitate data mining.
- Train graduate and undergraduate students in analytical techniques relevant to research work performed.
- Develop and maintain data storage, organization, and processing capabilities of the on-going research projects.
The candidate will have access to high performance computing resources of the KSU Beocat cluster (http://www.beocat.cis.ksu.edu/beocat), modern genomic instrumentation through the KSU Integrated Genomics Facility (http://www.ksre.ksu.edu/igenomics) and have a chance to interact with vibrant KSU research programs in plant genetics and genomics. For details about position please contact Eduard Akhunov (firstname.lastname@example.org).
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