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Postdoctoral Fellow, Department of Forest Resources
Open for Recruitment: March 25, 2010 - April 25, 2010
Announcement #: 12508058435
Salary Range: $32,500.00 -$36,000.00
Full or Part Time: Full Time
Location: Moscow
This position is contingent upon the continuation of work and/or funding.
Materials Required:
Online Application (click to apply)
Job References
Letter of Qualification
Resume
We are seeking a successfully completed PhD student to work with an interdisciplinary team of scientists to analyze a large forest stand database (>10,000 plots) from private, state and federal forest land holders in the Intermountain West and to develop geospatial site type models for assessing site quality. Additional biometric research will focus on 30 yrs of legacy Intermountain Forest Tree Nutrition Cooperative (IFTNC) datasets in forest nutrition and productivity. The project is funded through the IFTNC http://www.cnr.uidaho.edu/IFTNC/.
Responsibilities:
Research: Percentage of Time: 60 Essential
Responsibilities include: 1) compiling stand inventory data from public and private forest lands; 2) developing stand density and G&Y models that incorporate inputs of climate, soil, geology, and landscape as measures of resource availability; 3) predicting site productivity geospatially; and 4) analyzing growth response data from forest nutrition research.
Presentation of Research Results:
Percentage of Time: 30% Essential
Responsibilities include: 1) Preparing technical reports and peer-reviewed publications; and 2) Participating in technology transfer activities with cooperating forest land managers.
Other Support: Percentage of Time: 10% Marginal
Minimum Qualifications:
The post-doctoral fellow should have strong statistical skills in current biometric modeling methods; methods for assessing forest productivity; and knowledgeable of above and belowground processes controlling variation in productivity and stand density in forested systems. Willing to conduct field work in managed forests and strong verbal and written communication skills are critical. Evidence of statistical knowledge and ability to publish research results in refereed journals is required. PhD in a natural resource field: forest biometrics, forest management, forest ecology, or related fields.
Additional Desirable Qualifications:
Familiar with geospatial analysis tools (GIS, remote sensing, GPS); familiar with stochastic frontier analysis in its application to forest stand density models; multiple adaptive regression splines; and geographically weighted regression analysis
