Research Scientist

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Work type:Research Faculty
Senior management: Agriculture & Life Sciences
Department: School of Plant & Environmental Sci
Location:Blacksburg, Virginia
Categories:Agriculture / Life Science

Job Description

The School of Plant and Environmental Science at Virginia Tech is seeking a highly motivated research scientist to lead the barley breeding efforts within the small grains breeding program at Virginia Tech under the mentorship of the program lead. The applicant is expected to develop and apply novel breeding methods using high-dimensional genomic information and high-throughput phenotyping. The successful applicant is expected to lead all barley breeding efforts within the program as well as research projects as a principal investigator related to development of new barley varieties adapted to the eastern United States.
The successful applicant is expected to apply advanced modeling techniques to phenotypic, genomic and environmental data to drive breeding decision making. The successful applicant will lead breeding research projects related to barley development, serving as PI with the small grains breeder serving as Co-PI. The applicant will serve as a mentor to teach methods and technique to graduate students conducting research in barley breeding.

Required Qualifications

Ph.D. in plant or animal breeding, population or quantitative genetics, and experience in a crop breeding program; Ability to work as a team member, excellent oral and written communication skills, demonstrated ability to present information in public forums, excellent time management and organizational skills, and the ability to work safely in an agricultural environment. Must have a demonstrated record of publication in peer-reviewed journals and experience in cultivar development.

Preferred Qualifications

Development of cultivars, knowledge in mixed models, genomic prediction, sequence alignment and variant calling methods, proximal sensing, significant programing proficiency in a suitable scientific language (Python, Julia, R, C, C++, Fortran, etc.), machine learning, and knowledge or familiarity of crop management and field research techniques.

Salary Information

$61,625 - 80,000

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges , a school of medicine , a veterinary medicine college, Graduate School , and Honors College . The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers . A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Dr. Nicholas Santantonio at [email protected] during regular business hours at least 10 business days prior to the event.