"Post-Doctoral Associate"

About the Job

This is a full-time (100%) post-doctoral position with possibility of reappointment. 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.

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 have genotyped approximately 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). (45%)
• *Note: Please copy/paste the above link in your search browser, as clicking may provide an error message.*
• Conduct statistical analyses to examine differences in morphology, SWD infestation, and fecundity among taxa. (30%)
• Prepare peer-reviewed publications, reports, and stakeholder guides on native and nonnative honeysuckles and SWD. (15%)
• Supervise undergraduate researchers. (5%)
• Attend and present at regular individual and group meetings. (5%)

Supervisor of Position

Professor Alan G. Smith, Department of Horticultural Science

Qualifications

Required Qualifications

• Ph.D. in Genetics, Computational Biology, Bioinformatics, Agronomy, Horticulture, or related field in genome analyses
• Demonstrated experience in population genetics using genome-wide SNP datasets (e.g., DArTseq, GBS, RADseq, or similar reduced-representation sequencing and analysis using STRUCTURE, dartR, PCA, SplitsTree)
• Proficiency in statistical analysis and interpretation of complex biological datasets
• Working knowledge of statistics and software for the analysis of genome-wide SNP data (STRUCTURE, dartR, PCA, SplitsTree)
• Valid driver’s license, or acquisition within one month of hiring date.
• Excellent organizational skills and experience with large data sets.

Preferred Qualifications

• Publications or thesis on the genetic structure of organisms and diversity from genome-wide SNP markers generated via reduced representation sequencing (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, especially to stakeholders, funding agencies and the general public summarizing research findings
• Excellent communication skills, with ability to translate complex computational findings to diverse stakeholders

Pay and Benefits

Pay Range: $65,000 - $70,000 annually; depending on education/qualifications/experience

Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training
• Medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and life insurance
• Employee wellbeing program
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost

How To Apply

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will have the opportunity to complete an online application for the position and attach a cover letter and resume or CV.

Please include the following materials in your application:

• Cover letter and transcripts, CV with emphasis on genome-wide SNP data analysis and statistical analysis in R
• List of publications with the applicants’ contributions
• Writing sample, published or submitted manuscripts preferred
• Contact information for 3 references

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-8647.