Hcsu Postdoc Rsrch Analyst

HCSU POSTDOCTORAL RESEARCH ANALYST (PLANT TRANSLOCATION) – # 226320

CLOSING DATE:
June 30, 2026, or until filled. Regular, Full‑Time, RCUH Non‑Civil Service position with the Hawai`i Cooperative Studies Unit (HCSU) at the University of Hawai‘i at Hilo (UHH) in collaboration with the United States Geological Survey Pacific Island Ecosystems Research Center (USGS PIERC). Work location is in the USGS PIERC office in Hawai‘i Volcanoes National Park on the island of Hawai‘i.

Continuation of employment is dependent upon program/operational needs, satisfactory work performance, availability of funds, and compliance with applicable Federal/State laws.

MONTHLY SALARY RANGE: $5,833 - $6,250/Mon.

We are hiring a postdoc to help develop the analytical backbone of an applied conservation research effort focused on Hawai‘i's rarest plant species. Rare plant managers across the state are watching the landscape shift beneath their feet as climate, fire, and invasive pressures intensify, and they need better tools to understand where they can focus out planting, one of the primary conservation actions at their disposal.

We are looking for someone to help develop and refine species distribution models, build out planting performance models that link survival data to environmental conditions, and work with messy, real‑world monitoring datasets from across the state's rare plant conservation network. The work spans everything from machine learning and climate perturbation analysis to building R Shiny tools that put results directly in the hands of conservation managers making planting decisions.

This position will work with rare plant experts, field practitioners, and data managers across multiple islands and institutions, to collectively shape the priorities for climate‑resilient out planting efforts to safeguard multiple endangered/threatened plants.

Works with the Pacific Islands Ecological Research Center (PIERC) project leader and multi‑agency team to develop and apply species distribution models (SDMs) using machine learning and statistical methods to predict habitat suitability for rare Hawaiian plant species under historical, current, and perturbed climate conditions. Builds out‑planting performance models linking survival and vigor data from field monitoring programs to environmental covariates at planting sites.

Conducts climate sensitivity and perturbation analyses to distinguish climate‑resilient sites from climate‑vulnerable ones. Integrates and harmonizes out‑planting monitoring data from multiple partner organizations (USFWS, PEPP, ANRPO, PTA, NPS) that vary in structure, completeness, and quality. Works with partner database and data managers to compile, clean, and standardize datasets for analysis. Collaborates with PEPP coordinators and field practitioners to incorporate expert knowledge into modeling workflows, including expert‑source performance categories and practitioner‑selected reference sites for microhabitat matching.

Produces spatial data products, maps, and interactive tools (e.g., R Shiny applications, web maps) to communicate model outputs to conservation managers. Contributes to peer‑reviewed publications, technical reports, and presentations summarizing analytical methods and results. Assists with preparing all research products for the USGS policy and quality reviews, such as Fundamental Science Practices (FSP). Uses AI‑assisted tools (large language models, AI coding assistants, and related technologies) as a regular part of the analytical workflow to accelerate code development, support statistical reasoning, improve writing quality, and maintain high productivity across all project tasks.

PhD from an accredited college or university in Ecology, Geography, Conservation Biology, Statistics, Data Science, or other related field.

One to three (1‑3) years of experience working with R for ecological or geospatial analysis.

Includes at least one (1) year of experience in each of the following:

• building, training, and evaluating species distribution models or comparable spatial ecological models;
• working with geospatial data including raster and…