Project Information: This position is focused on nonnative and native Lonicera (honeysuckles), their genetic structure, identification, fecundity and interactions with Drosophila suzukii (spotted wing Drosophila, SWD). Many of the nonnative Lonicera species invading Minnesota are not identified and are hybridizing, making management and regulation challenging. We genotyped 2,485 native and nonnative Lonicera individuals from 16 taxa using genome-wide markers generated via reduced-representation sequencing (DArTseq). This position will analyze genetic structure, assess species identification, and detect hybrids. Morphological data for identification, SWD infestation rates, and seed viability for the genotyped individuals were also collected. These data have direct applications to the management and regulation of nonnatives and the conservation of native Lonicera.

Duties/Responsibilities: • Conduct population genetic analyses of genome-wide SNP data, integrating results with geographic origin, key morphological traits, SWD infestation levels, and seed viability (see an example from our team’s research at https://doi.org/10.1002/ajb2.70124; or copy/paste the link in your search browser • Conduct statistical analyses to examine differences in morphology, SWD infestation, and fecundity among taxa • Prepare peer-reviewed publications, reports, and stakeholder guides on native and nonnative honeysuckles and SWD • Supervise undergraduate researchers • Attend and present at professional, group and individual meetings

Requirements: • Minimum highest degree of Ph.D. with proficiency in statistical analysis and programing in R Studio • Demonstrated experience in population genetics using genome-wide SNP datasets (e.g., DArTseq, GBS, RADseq, or similar sequencing and analysis using STRUCTURE, dartR, PCA, SplitsTree) • Proficiency in statistical analysis and interpretation of complex biological datasets • Working knowledge of software for the analysis of genome-wide SNP data (STRUCTURE, dartR, PCA, SplitsTree) • Excellent organizational skills and experience with large data sets • Valid driver’s license, or acquisition within one month of hiring date.

Preferred Skills and Training: • Ph.D. in Genetics, Computational Biology, Bioinformatics, Agronomy, Horticulture, or related field in genome analyses • Publications or thesis on the genetic structure of organisms and diversity from genome-wide SNP markers generated via reduced representation sequencing (e.g. DArTseq) using tools such as dartR, STRUCTURE, PCA, and SplitsTree • Knowledge of plant taxonomy, anatomy, and invasive plants • Grant management experience, including project timelines, personnel, and budgets • Demonstrated writing skills, such as peer-reviewed publications, grant proposals, and materials for lay audiences • Record of presentations, to researchers, stakeholders, funding agencies, and the public summarizing research findings • Excellent communication skills, with ability to translate complex computational findings to diverse stakeholders

Appointment: The initial appointment is for one year, beginning as soon as possible. Renewal for a second year is possible upon successful progress and continued funding Instructions: Please apply through UMN HR Job ID 371575.

Contact Alan G. Smith, smith022@umn.edu, with questions.