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Kansas State University
Posted: 10/11/2021
Fellow (Post Doc) - Plant Pathology
Fellow (Post Doc) - Plant Pathology

Department: 3670010110 Plant Pathology
Job no: 511525
Employment type: Post Doc (Term)
Location: Manhattan, Kansas
Categories: Agriculture, Research / Scientific / Grants, Natural / Quantitative Sciences, Plant Sciences
Pay Grade: 001

About This Role:
The Akhunov Lab in the Department of Plant Pathology, KSU is seeking a Fellow Post-Doc. We look for a highly motivated, creative and open-minded candidate interested in integrating genetics, functional genomics, evolutionary biology and genome editing to map and characterize genes and pathways underlying variation in disease resistance and/or productivity traits in wheat with the final goal of applying this knowledge for crop improvement.

Specific duties include:

• Design genetic mapping experiments aimed to associate genetic variation with phenotypic variation to identify factors contributing to trait variation in wheat; develop experimental populations (bi-parental mapping populations, diversity panels, mutant populations) to map and validate the effects of genetic variants on phenotype; collaborate with other members of a team to facilitate on-going field and greenhouse-based gene mapping projects; maintain detailed records of experiments performed.

• Analyze and prepare data for publication in peer-reviewed journals; prepare manuscript drafts in collaboration with project PI and other members of the project team; collaborate with the lab PI on the preparation of manuscripts for publication in the peer-reviewed journals; work with the lab PI on the preparation of progress reports to granting agencies.

• Train graduate and undergraduate students in the analytical techniques relevant to research work performed; work with the PI and students to create a positive learning environment in the lab; work with the graduate students and PI on preparing paper presentations for a journal club and scientific meetings; help graduate students with the preparation of research work for publication.

• Prepare data in the formats suitable for deposition to public databases; collaborate with a bioinformatical scientist to deposit the results of analyses to the laboratory and public databases.

• Coordinate with other members of the team phenotyping experiments in the field and greenhouse.

The successful candidate will have recent Ph.D. level training in plant genetics/genomics, crop breeding, plant biology, or related fields with the demonstrated potential to integrate experimental and analytical approaches to map and functionally characterize causal genes/pathways controlling phenotypic traits. While a strong background in statistical and bioinformatical approaches applied to analyze complex datasets including next-generation sequence data is desirable, a candidate is expected to develop projects in collaboration with a bioinformatics scientist in the Akhunov Lab. Excellent organizational, written/verbal communication skills and the ability to work in a multicultural environment is required. Knowledge of coding in one of the major languages used for statistical analyses or analyzing genetic and genomic data would be a plus.

Why Join Us:
In this position, you will have access to high-performance computing resources of the KSU Beocat cluster (, modern genomic instrumentation through the KSU Integrated Genomics Facility ( and have a chance to interact with vibrant KSU research programs in plant and fungal genetics and genomics. For details about the position please contact mailto:(

Kansas State University offers a comprehensive benefits package that includes health insurance, life insurance, retirement plans, paid time off - vacation, sick, and holidays. To see what benefits are available, please visit:

We Support Diversity and Inclusion:
Kansas State University embraces diversity and inclusion. The university actively seeks individuals who foster a collegial environment and cooperative interactions with coworkers, students, and others. The University is dedicated to promoting the

What You'll Need to Succeed:
Minimum Qualifications:

• Requires a Ph.D. degree and three or more years of experience in the fields of plant genomics/genetics, plant biology, or crop breeding with hands-on training in analyzing genomic and phenotypic datasets.
• Experience with integrating various types of genetic and genomic data to identify genes/pathways controlling phenotypic trait variation in plants.
• Strong background in statistical and bioinformatical approaches applied to analyze complex datasets including next-generation sequence data.
• Excellent organizational, written/verbal communication skills
• ability to work in a multicultural environment

Preferred Qualifications:

• Familiarity with functional genomics tools and resources used for validating gene function in major crops (wheat, barley, maize, rice, or sorghum).
• Knowledge of computer programs for the analysis of genetic and genomic data.
• Knowledge of at least one programming language (Perl, Python or Java).
• Ability to perform statistical analyses in SAS, or R.

How to Apply:
Please submit the following documents:

• CV with a list of publications
• Statement of Research Interest
• Contact information for at least three professional references.
Screening of Applications Begins:
Screening begins immediately and continues until the position is filled. For best consideration, apply by October 15, 2021

Anticipated Hiring Salary Range:
$47,500 -$ 62,000

Equal Employment Opportunity:
Kansas State University is an Equal Opportunity Employer. All applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender, gender identity, age, national origin, disability or status as a protected veteran.

Background Screening Statement:
In connection with your application for employment, Kansas State University will procure a Background Screen on you as part of the process of considering your candidacy as an employee.

Advertised: Sep 29, 2021

Application Closes: Open until filled

To apply, visit

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