Job Description
Texas A&M AgriLife Research seeks an outstanding, innovative, and dynamic research faculty in Forest Management and Natural Resources Modeling Research at the rank of Assistant Professor.
This appointment will be 12 months, non-tenured, % Research, and administratively located with Texas A&M AgriLife at the Blackland Research and Extension Center in Temple, Texas.
In addition, will be affiliated with the Department of Ecology and Conservation Biology at Texas A&M University, College Station, TX.
The applicant will work closely with other scientists within the department, Texas A&M University, Texas A&M AgriLife Research, Texas A&M Forest Service and Texas A&M AgriLife Extension to build a highly impactful, externally funded, nationally recognized, and self-sustainable research program that addresses issues facing the forestry industry in Texas related to productivity and sustainability.
Position Responsibilities / Duties :
Build an externally funded, nationally recognized, self-sustainable research program that addresses issues facing the forestry industry in Texas related to productivity and sustainability.
- Address the researchable issues related to 1) Reforestation and land management to produce crops and timber; 2) Utilization of wood and forest products;
- 3) Forest and rangeland management to produce forage for domestic animals and wildlife; 4) Forest protection against wildfire, pest and destructive agents;
5) Watershed management and water quality of forest areas; and 6) Forest management for recreation purposes. Each research experiment / activity will be focused on one or more of the topics listed but will be designed to also evaluate impacts on environmental sustainability including measures of greenhouse gas emissions and soil health parameters.
These duties require operating a vehicle.
Research data, algorithms, and models will be obtained from government, university, and industry sources, including other Blackland / Grassland team members and their collaborators nationwide and worldwide.
The candidate will be expected to develop and improve algorithms and models, disseminate findings, train graduate students, and secure external funding.
Results will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest management communities.
Engage with industry professionals and cooperate in outreach activities relevant to stakeholders.
Work with the Texas A&M Forest Service and District Foresters, Texas Forestry Association, county extension agents, on-campus and other state-wide faculty, and other forestry professionals in the region and participate in activities of relevance to stakeholders.
Participate in appropriate programming to contribute tangible impacts on the economic viability and competitiveness of the Texas Forestry Industry.
Required Education / Experience
Ph.D. in an area of Forest Science or a closely related field by hire date.
Experience with forest production and management practices and related activities.
Strong quantitative skills related to forest management research, including expertise in biometrics, modeling, and geospatial analysis.
Record of peer-reviewed publications of original research.
Valid drivers’ license / ability to obtain a valid driver’s license.
Preferred Education / Experience
Prior academic, post-doctoral, or professional experience.
Prior research experience on production forestry.
Experience working with federal agencies or in other multi-agency collaborative settings.
Modest teaching experience that will enhance graduate student success.
Modest outreach experience with stakeholder interaction.
Grant writing experience and evidence of the ability to attract external funding.
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Texas A&M AgriLife Research seeks an outstanding, innovative, and dynamic research faculty in Forest Management and Natural Resources Modeling Research at the rank of Assistant Professor. Work with the Texas A&M Forest Service and District Foresters, Texas Forestry Association, county extension agen...
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