IMPORTANT: This Advertiser has requested that applicants MUST be National Residents / Valid Work Permit-holders. Other applicants need not apply.
Job Description
This position has opportunity for growth in the field of the human dimensions of global environmental change. The successful candidate will combine quantitative analysis skills and knowledge of impacts, vulnerability, resilience, and/or adaptation to global change. Depending on the incumbent, assignments will fall in two broad areas:
1. Indicators of vulnerability and resilience to global change impacts: Participate in research program to continue development of indicators for use in analysis and management of vulnerability/resilience to global environmental change. Conduct case study research on socioeconomic and environmental impacts of climate change. Identify generalizable relationships across case studies to develop quantitative analysis of vulnerability and resilience. Research indicator methods.
2. Scenario development and application: Participate in research program to develop new socioeconomic scenarios and participatory scenario methods for assessing adaptation to global environmental change. Assignments will involve quantitative and qualitative analysis of historical trends and projections of population growth, economic development, human development, and other factors.
Minimum Requirements
Candidates must have received a PhD within the past five years from an accredited college or university. All staff at the Pacific Northwest National Laboratory must be able to demonstrate the legal right to work in the United States.
Qualifications
- Knowledge of approaches for analysis of impacts, vulnerability, resilience, and adaptation to global environmental change; alternatively, the knowledge of socioeconomic development or other related areas
- Quantitative skills related to development of composite social and environmental indicators including Identifying and gathering data, organizing and working with data sets, imputing missing data, multivariate analysis (e.g., principal components, factor analysis, etc.), normalization of data (e.g., standardization, transformation, etc.), aggregation and weighting, uncertainty and sensitivity analysis, data visualization
- Use of geographic information systems (optional)
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