Initial appointment is for one year with possible extension. Salary: $32,000 - $42,000 depending on experience. _To Apply_: Send printed or electronic (preferred) copies of (1) curriculum vitae; (2) names and contact information (phone, email) three references; and (3) reprints of up to three publications to: Dr. Max Moritz, Department of Environmental Science, Policy and Management, 137 Mulford Hall, MC 3114, Berkeley, CA 94720-3114, [EMAIL PROTECTED] (please copy [EMAIL PROTECTED]).
A post-doctoral research position in fire ecology and spatial modeling
of current and future fire regimes is available in the College of
Natural Resources at the University of California, Berkeley in
association with the Center for Fire Research and Outreach
(http://firecenter.berkeley.edu) and the lab of Dr. Max Moritz
(http://nature.berkeley.edu/moritzlab). Responsibilities include
analysis of biophysical constraints on historical fire patterns using
statistical approaches, predictive modeling of future fire regimes under
global change scenarios, processing fire-related spatial data from a
variety of sources (e.g., remote sensing, GIS) at multiple scales,
publishing research results in peer-reviewed journal articles, and
future funding proposal development. Strong statistical (e.g., GAMs) and
spatial analysis skills will be employed on regular basis. There will be
close interaction with others working on fire ecology, conservation,
climate change research (e.g., related to projects with The Nature
Conservancy), with an emphasis on spatial fire probability mapping for
use in carbon sequestration and emissions-related modeling projects
(e.g., carbon accounting in fire-prone ecosystems).
Applicants should have a completed or imminent Ph.D. in species
distribution modeling, applied statistics, biogeography, computational
ecology, fire ecology, or related field. Very strong statistical and
computer skills required; excellent written and verbal communications
skills also required. Training and experience in geospatial technologies
such as GIS and related programming skills are important, as is
familiarity with spatial sampling design (e.g., how assumptions about
presence/absence/suitable but unused observations affect estimates).
Knowledge of remote sensing, disturbance ecology, and/or forest ecology
is desirable. Ability to work with non-governmental organizations as
part of a larger team, but also to work independently, is essential.
