Open Position: Postdoctoral Scholar

The Brosi Lab at the University of Washington, Seattle is seeking a postdoctoral scholar to work on: 1) quantitative DNA metabarcoding of pollen, supported by a recent NIH grant; AND 2) field ecology projects on plant-pollinator interactions, supported by foundation grants. Thus, we are seeking a post-doc who has both strong molecular ecology / molecular biology experience and also strong field work experience. The Brosi lab strives for a dynamic, productive, and positive work environment and we welcome applications from individuals with a wide range of backgrounds. We seek applicants that will contribute to our positive and productive lab environment, that wish to grow their mentorship skills, and that will efficiently produce scientific papers. Our NIH project is in close collaboration with a biostatistician and we will prioritize applicants who are enthusiastic about contributing to this collaboration.

Position details

We are looking for this position to begin ASAP, but will consider applicants who can start later, up to March 1, 2027, especially for applicants that could spend at least one (paid) week in Seattle prior to December 18, 2026. The position will be funded for one year, with at least one year of additional funding (and potentially more) pending satisfactory performance. We will prioritize applicants that can commit at least two years in the position.

The position is in-person and requires lab work at the University of Washington and field work in Washington State (among other potential locations). We will not consider applicants desiring to work remotely; please do not inquire about remote work possibilities.

The minimum salary for the position is set by the UW post-doc union contract; the current minimum salary is just over $68,400 a year and the position includes a generous benefits package. Teaching is not a requirement of the position but it may be a possibility in some circumstances if there are opportunities and if teaching is aligned with the post-doc’s career goals.

How to apply

Submit the following components to this Google Form:

• a cover letter addressing how your background relates to the preferred qualifications described below (.pdf format, < 1 MB)
• a CV (.pdf format, < 1 MB)
• three professional references including contact information (.pdf format, < 1 MB)
• a statement on AI use in developing your application (short answer text; paste into the form)

We will begin reviewing applications the morning of October 28, 2026, and applications received by then will receive priority, though we will continue reviewing applications until the position is filled.

Please do not contact Dr. Brosi to ask for more details on the position, introduce yourself, highlight your application, or to describe your interest in or fit for the position—instead do that through the application described above. We will carefully review all applications. For substantive questions related to the position (only), you may contact Prof. Berry Brosi at bbrosi {-at-} uw [dot] edu.

Minimum requirements

• PhD in Ecology, Biology, or related field earned by the time of application or fully completed no longer than two months after beginning the position
• Ability to walk up to 10+ miles in one day in challenging terrain including at elevations over 9,000 feet while carrying up to 40 pounds, across a range of temperatures and potentially inclement weather

Strongly preferred qualifications

We are unlikely to consider applicants who do not meet all of these requirements.

• Extensive experience in basic molecular biology methods including basic DNA isolation, PCR, sequencing, etc., including experience with molecular biology laboratory troubleshooting
• Strong experience with terrestrial ecological field research
• Basic proficiency in data / statistical programming, preferably in R
• Excellent written and verbal communication skills
• A strong track record of, or potential for, efficiently producing peer-reviewed scientific publications

Preferred qualifications

We do not expect that any one applicant will have all of the preferred qualifications for this position. If you meet all of the “strongly preferred qualifications” above, but only some or even none of the preferred qualifications below, please still consider applying. The preferred qualifications below are in no particular order.

Mentorship

• Experience with and demonstrated commitment to mentorship of research contributors at different stages, including undergraduate and graduate students, RAs, and volunteers among others
• Leadership of teams of research contributors in both laboratory and field settings

Laboratory work

• Strong laboratory work documentation skills for replicable lab work
• Flow cytometry experience
• Substantive experience with pollen or other DNA metabarcoding

Statistical and computational skills

• Strong skills (not just basic proficiency) in data / statistical programming in R (preferred) or other languages such as Python
• Bioinformatics experience, especially with the DADA2 package and/or Bioconductor in R
• Experience with using GitHub as well as practice developing and using strong replicable data workflows
• Experience working with phylogenies
• Experience working with ecological network data analyses
• Experience working with mapping/geographic information packages in R
• Ability—or interest in growing—to use LLM / AI tools thoughtfully, intentionally, and responsibly

Field biology

• Extensive terrestrial fieldwork experience, including both designing and carrying out field ecology projects
• Fieldwork experience with pollinators and/or plants (especially plant-pollinator networks), particularly in the montane Western US
• Fieldwork in agricultural settings, particularly for plant-pollinator interactions
• Identification skills of bees and other pollinators and/or plants
• A valid US or international driver’s license

Other skills

• Experience with mathematical and/or computational ecological modeling and especially data-theory integration
• Interest in and experience with applying for external research funding