Spatial Data Scientist

Position summary

The FOCAL Lab at UC Davis is recruiting a Spatial Data Scientist to contribute to the lab’s work at the intersection of disturbance ecology, forest mapping, and forest management. The Scientist will develop scripted analytical workflows and tools to analyze large geospatial datasets. The majority of the Scientist’s work will support the Open Forest Observatory, a new NSF-funded project on the frontier of drone-enabled forest ecology. The OFO is building open-source tools to (a) map forests at the individual-tree level using low-cost drone technology and (b) make the resulting maps publicly available. The Scientist will also lead or co-lead other data-intensive lab projects, with an initial focus on a collaboration with USGS that aims to understand fine-scale variation in tree mortality in areas of recent large wildfires in California by analyzing high-resolution imagery (drone, airplane, and satellite) and plot-based field data.

Strong background in reproducible, scripted (e.g., R- and/or Python-based), open-source geospatial processing and statistical or machine-learning analysis of large datasets is required. Experience with deep learning for computer vision is desired and will aid in development of OFO modules for tree species ID from drone imagery and other imagery interpretation tasks. An ecology background is preferred, but most important is a strong data science background. In addition to analysis and code development, the Scientist will be expected to lead, co-lead, or contribute substantially to the preparation of scientific publications and to the dissemination of results via workshops and presentations. The Scientist will report to FOCAL Lab PI Derek Young and will work closely with collaborators at USGS, CU Boulder, U of Arizona, CyVerse, and other institutions.

Hours, dates, and work location

The preferred start date is January - March 2023, but there is potential to accommodate a start date as late as September 2023. The position is full time. The position is intended to be a career-track role and will be renewed in 1-2 year increments. Depending on the start date, the Scientist may initially be appointed to an hourly position (with commensurate hourly rate) while the salaried position is finalized. The position may be remote or in person (office on the UC Davis campus) depending on preference.

Compensation

  • Applicants with a master’s degree: $56,300 - $62,000 depending on experience
  • Applicants with a PhD: $63,000 - $72,000 depending on experience

Primary duties

  • In collaboration with the supervisor and other OFO collaborators, improve upon existing OFO methodologies (e.g., 1, 2, 3) to develop scripted (automated) workflows for processing drone imagery into individual tree-based forest maps, optionally employing deep learning computer vision models
  • Calibrate and validate forest mapping workflows by comparing drone-derived forest maps to extensive field-based forest inventory data, including NEON data
  • Develop the infrastructure for a searchable index (“metadatabase”) of drone-derived forest maps produced by the OFO and contributors (prototype)
  • Employ high-performance computing and data storage platforms including Jetstream2 and CyVerse for large analyses and to deploy tools for third-party use
  • Package scripted workflows into user-friendly software libraries
  • Lead the analysis of large geospatial datasets to address ecological research questions, including data processing and statistical and/or machine learning modeling
  • Adapt/refine the analytical approaches developed by the PIs, with potential to incorporate additional questions of interest
  • Rigorously document analytical approaches and workflows to facilitate repeatability
  • Lead, co-lead, or contribute substantially to the preparation of scientific manuscripts and code and data releases
  • Present results at academic and/or natural resource management conferences
  • In collaboration with the supervisor, develop funding opportunities to further the research goals of the FOCAL Lab
  • Mentor junior lab members in data science tasks

Minimum qualifications

  • Master’s degree in ecology, remote sensing, computer science, or related field
  • Proficiency with data processing and statistical modeling in R and/or Python
  • Proficiency with scripted geospatial analysis in R (e.g., using the ‘terra’, and ‘sf’ packages)
  • Experience working with very large empirical (tabular) and geospatial vector and raster datasets
  • Experience collaborating via GitHub or equivalent

Desired qualifications

  • Understanding of and interest in forest ecology and disturbance ecology concepts
  • Experience developing interactive websites and web applications
  • Evidence of ability to publish research results in peer-reviewed journals

To apply

Please combine a cover letter (including preferred start date), CV, and contact information for three references into a single PDF and email to Derek Young, djyoung@ucdavis.edu, and Phil van Mantgem, pvanmantgem@usgs.gov. Use the following subject line: Spatial Data Scientist. Application review will begin on December 9, 2022, and will continue until the position is filled.