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Postdoctoral Scholar in Ecological Modeling (Forests)

Position overview

Position title: Postdoctoral Scholar
Salary range: See Table 23 for the salary range for this position. A reasonable estimate for this position is $60,000 - $ 71,952.
Percent time: 100%
Anticipated start: Start date is negotiable between October 30, 2023 and January 15, 2024
Position duration: The initial appointment will be for two years and is potentially renewable, depending on performance and availability of funding.

Application Window

Open date: August 18, 2023

Next review date: Thursday, Sep 28, 2023 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.

Final date: Friday, Oct 20, 2023 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

Position description

A two year plus postdoc position on climate impacts on conifer reproduction is available at UC Merced in the Moran lab [https://sites.google.com/site/moranplantlab/ ]. Our research focuses on the ecological and evolutionary responses of forests to climate change.

This project makes use of the Mast Inference and Forecasting (Mastif) model, and the associated global network of forest monitoring plots. This network of research collaborations has already yielded multiple high-impact papers. The Moran lab is currently participating in an NSF-funded grant^ that aims to build on this work by linking data on seed production to consumer/disperser activity and seedling growth and establishment. We also recently received funding from a UC climate change research initiative for a project that, among other things, aims to use this model framework to better target seed collection efforts for reforestation.

Duties of the postdoc would include:

  • Assisting with collection (fieldwork) and management of cone count and seed trap data from across California and beyond. This will include mentoring undergraduate research assistants
  • Analyzing California tree fecundity data using the Mastif framework to test how seed production is affected by tree size, climate, and multi-annual mast cycles, and how these relationships vary by species or genera.
  • Collaborating with UC Davis team-members to develop web-based tool to share the resulting fecundity predictions with forest managers.
  • Participating in meetings with research teams and stakeholders (all UCOP project meetings, NSF project meetings as desired).
  • Taking active part in manuscript preparation. At least one manuscript will be the primary responsibility of the postdoc as first author. The postdoc will also give at least one presentation on this research at a professional meeting.

The postdoc would also be encouraged to propose additional independent analyses using these datasets that match their research interests.

Qualifications

Basic qualifications

Candidates must have completed a PhD in biology, ecology, mathematical modeling, or similar discipline, and have substantial experience with R. The candidate must be creative, self-disciplined, and motivated (as evidenced by reference letters, prior research productivity, and any research questions suggested in communication with PI).

Preferred qualifications

Experience with Bayesian modeling is highly desirable, but not strictly required. Fieldwork experience, or at least outdoor experience (hiking, camping, etc.), is likewise desirable but not strictly required.

Application Requirements

Document requirements
  • Curriculum Vitae - Your most recently updated C.V.

  • Cover Letter

  • Statement on Contributions to Equity, Diversity, and Inclusion - Statement on your contributions to equity, diversity, and inclusion, including information about your understanding of these topics, your record of activities to date, and your specific plans and goals for advancing equity and inclusion. Please review the UC Merced Diversity Statement Guidelines and UC’s Commitment to Diversity

Reference requirements
  • 3 required (contact information only)
Apply link: https://aprecruit.ucmerced.edu/JPF01618

Help contact: snspersonnel@ucmerced.edu

Campus Information

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements. This includes the University of California Policy on Vaccination Programs: https://policy.ucop.edu/doc/5000695/VaccinationProgramsPolicy.

The University of California is an Equal Employment Opportunity/Affirmative Action employer and invites applications from all qualified applicants, including women, minorities, veterans, and individual with disabilities, who will enrich the teaching, research and public service missions of the university. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy, see: UC Nondiscrimination & Affirmative Action Policy (https://policy.ucop.edu/doc/4000376/DiscHarassAffirmAction).

The University of California, Merced, is the newest of the University of California system’s 10 campuses. With over 9,000 undergraduate and graduate students (https://www.ucmerced.edu/fast-facts), UC Merced provides outstanding educational opportunities to highly qualified students from the heart of California, the nation, and abroad. The campus has special connections to nearby Yosemite National Park; is on the cutting edge of sustainability in construction and design; and supports the economic development of Central California. The Merced 2020 Project doubled the physical capacity of the campus, and enhanced academic distinction, student success, and research excellence (https://merced2020.ucmerced.edu/).

UC Merced is a smoke & tobacco free campus (https://smokefree.ucmerced.edu/).

Job location

Merced, CA