The Department of Geography at the University of Alabama is accepting applications for a one-year research assistantship in political ecology with the possibility of renewal for the pursuit of a doctoral degree. The assistantship provides a stipend plus tuition remission.
The successful applicant will work with me and will be involved in political ecology projects focused on human dimension of climate change, community resilience to climatic hazards, environmental hazards and public health in the U.S. in general and the U.S. Gulf Coast in particular.
Qualified candidates should have a Master’s degree in Geography, Environmental Studies/Sciences, Planning or a related discipline. Candidates should have a strong interest in the intersection of social, political, and physical dimensions of climate change and be eager to work in an interdisciplinary environment. Experience in quantitative data analysis and geographic information systems (GIS) are desired. Strong oral and written communication skills are required.
For more information about this assistantship, please contact me at email@example.com well in advance of February 15, 2019 (the application deadline). Please include a copy of your CV, unofficial academic transcripts, and a brief personal statement that highlights skills relevant to the position.
For more information about the department, please see https://geography.ua.edu/.
William Nordhaus was awarded the Nobel Prize in Economic Sciences because of his decades' effort to integrate climate sciences into economic models. His Dynamic Integrated Climate and Economy (DICE) is used to explain how Greenhouse Gases emissions if not tamed could lead to catastrophes down the road. This pioneering effort is not immune to criticism. Using climate-economy integrated models to design and implement specific climate policies is subject to misuses, as Robert Pindyck contended. According to Pindyck, modeler's limited knowledge about climate sensitivity and arbitrary selection of functional forms and parameter values do not make results from complicated models more valid than modeler's own "expert" opinion.