Flood Risk Research: GIS and/or Applied Statistics/Economics
We are seeking expressions of interest in a potential research position at the Center for Watershed Sciences at University of California at Davis (UCD). An active researcher/analyst is sought to join a team working with large geospatial databases and GIS in order to assess flood risk and other natural hazards. The position is at the post-graduate level (complete MS or PhD in hand). At present we are open to several position options, including: either (1) a staff researcher position or (2) a full-time post-doctoral research position ("Researcher" type job title), or potentially (3) a doctoral student assistantship (50% GSR) while the student pursues a PhD at UCD.
Our research group is working primarily with large flood- and hazard-related datasets with a geographical component. The successful candidate will have demonstrated research experience and research-level technical skills in one of the two following areas: (1) Geographic Information System GIS) analysis, or (2) Multivariate Statistical analysis of large real-world datasets, preferably applied to economic questions. Expertise with both of these areas would be a plus.
The project will involve manipulating and analyzing large, complex, and spatially explicit datasets. These data sets and our research are related to flood risk, floodplain management, natural hazards analysis, and science-driven policy.
The successful applicant should have the following:
• A Masters or PhD degree in GIS, Statistics, or Economics, preferably in geography, hydrology,
engineering, geology, applied statistics, or applied economics
• In the area of GIS – Strong working knowledge of desktop GIS , experience with geo/GIS standards
and tools required; experience with a programming or scripting language, such as Python, R, C#, or
C++ is preferred.
• In applied statistics or economics – Strong working knowledge and demonstrated experience with
statistical packages, such as R, SAS, and/or SPSS required. Experience with SQL, scripting or coding
(e.g., Python, R, etc.) is preferred. Experience with data visualization and development of models
based on data is desired.
• Ability to manage and integrate large and complex spatially explicit datasets is required; experience
with flood, water, or hazards data would be a plus.
• Potential for academic growth demonstrated by: journal publications, scientific meeting
presentations, funding proposals, and/or technical reports completed or in progress.
• The successful candidate should be a citizen or permanent resident of the USA
Expressions of Interest: Interested persons should send an expression of interest to
email@example.com no later than June 15, 2018. Relevant background information such as a
current CV would be appreciated.