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Natural Resources Scientist-Senior and Forester-Senior - Limited Term Employment

  • Wisconsin Department of Natural Resources
  • 11/18/21
  • Rhinelander, WI
  • 54501
  • $19.46 - $24.33 / Hourly
  • Full-Time
The Wisconsin DNR is hiring an LTE Natural Resources Research Scientist-Senior and Forester-Senior located at the Rhinelander Service Center in Rhinelander, Wisconsin.

This dual LTE appointment is comprised of two 20-hour positions for an expected work schedule of 40 hours per week. The intention is to hire one candidate on both positions.

Position 1, Natural Resources Research Scientist-Senior:
This position will manage and analyze datasets and data requests for a wide variety of forestry research projects within the Division of Forestry, Forest Ecology and Economics section. Current projects are diverse and highly collaborative, focusing on research and application of science to forest ecology and management, which will provide the successful applicant many opportunities to grow and develop a varied skillset. Research within the section could include but is not limited to an assisted migration study in collaboration with the USFS to determine viable climate change mitigation techniques, a study of deer impacts on forest regeneration, and a collaborative study to determine the effects of mycorrhizal associations on forest health and small mammal communities. The highly collaborative nature of our research requires a data scientist with experience collating data from a wide variety of sources, working independently and as part of a team, statistical analysis, and building and maintaining databases to be utilized by internal and external partners.

60% -Data analysis and management:
- Building and managing project-specific databases
- Writing and executing queries
- Statistical analysis
- Spatial analysis
40% -Data summarization and report writing:
- Creating literature synthesis reports
- Creating 'white papers' summarizing the results of research for dissemination
- Creating summaries of ongoing projects
- Creating reports required by grant funded projects
- Assisting in preparing peer reviewed scientific manuscripts

Position 2, Forester-Senior:
This position within the Division of Forestry, Forest Ecology and Economics section will coordinate and conduct a variety of forestry work in the field including data collection and the set up and maintenance of study sites and related equipment. This position will design and implement spatial databases and perform spatial data analyses for a variety of forestry projects. Current projects within the section are diverse, highly collaborative, and utilize large spatial datasets. The position will use skills and technical abilities related to Arc GIS software and program R (or similar) to review and analyze spatial datasets, independently build geodatabases, and design apps for spatial data collection. The successful candidate will be expected to resolve technical problems and work independently to perform spatial data analyses. This position will also collate and enter field-collected data and performing data quality assurance measures. This field work will be a mixture of working independently and as a member of a team.

60% - Forestry Fieldwork and Fieldwork Preparation:
- Coordination and planning of forestry fieldwork
- Forest understory and overstory assessments
- Ground-truthing remotely sensed datasets
- Soil frost study site maintenance
- Deer browse assessments
- Data logger deployment and maintenance
- Long term project infrastructure maintenance
- Long term project establishment
- Seed collection
40% - Spatial database creation, maintenance, analysis:
- Design and implement spatial data inventory systems
- Develop and manage standard geographically based datasets
- Data preparation, QA/QC and entry
- Provide technical support to forestry research staff regarding use of GIS software
- Learn, operate, and provide recommendations on new database, data modeling, meta-data repository, GIS, reporting and other data management tools and methodologies
- Analyze spatial data using analyses recommended by forestry research staff

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