Apply by this date to ensure full consideration by the committee.
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
The Environmental Market Solutions Lab (emLab) (http://emlab.msi.ucsb.edu/) is a new interdisciplinary team of economists and scientists based at UC Santa Barbara dedicated to bringing market-based solutions to the world's most pressing environmental problems. We deliver cutting-edge research and innovative policy solutions by combining economic principles, ecological insights, and big-data analytics. We seek 1-2 postdoctoral researchers to participate in the development and execution of applied and/or academic research projects in environmental and resource economics. The successful candidate(s) will gain academic mentorship and research training in one or more of emLab’s focus areas in climate solutions, poverty alleviation, land use, and sustainable fisheries.
The ideal candidate(s) will have excellent quantitative and modeling skills and an interest and track record in publishing in top science and economics journals. The scholar(s) will have the opportunity to work with emLab principals Christopher Costello, Olivier Deschenes, Kelsey Jack, Kyle Meng, and Andrew Plantinga, and will report directly to the principal who most closely aligns with their area of research. Under the academic mentorship of the emLab principals one candidate will gain research training in the analytics for a new emLab project focused on estimating supply and demand curves for existing and new marine food sources. Both candidates will have the flexibility to focus on areas of emLab's research portfolio in which they are most interested in obtaining training, and they will also be able to allocate a fraction of their time to their own research.
● PhD in Environmental Economics, Natural Resource Economics, or a closely related discipline at the time of application.
A minimum of 2 years of academic or applied research experience in empirical economic methods and modeling related to fisheries, climate, land-use or poverty alleviation which includes:
● quantitative and modeling skills in R, Stata, and/or Matlab
● managing, processing, and analyzing large datasets
● An interest and track record in publishing in top academic journals
● Proficiency using Git, and other modern data management, sharing and presentation interfaces
● Experience with Geographic Information Systems
● Familiarity with high-performance server computing such as Google Compute Engine or AWS
● Proficiency with LaTeX
● Ability to balance a diverse portfolio of responsibilities simultaneously
● Excellent communication skills to contribute to reports and peer-reviewed scientific publications, deliver presentations, and translate scientific concepts for diverse audiences
● Strong interpersonal skills to build and maintain strong relationships with academic, NGO and government partners, and to work effectively as part of a highly collaborative research team.
This is a 100% time appointment. The duration of the initial appointment is 12 months; reappointment for an additional year(s) is possible depending on performance and funding. Start date is negotiable but ideally would be in the first quarter of 2019. Salary is competitive, commensurate with the applicant’s qualifications. Postdoctoral benefits are included (http://hr.ucsb.edu/benefits/postdoc.php).
Electronic applications including a cover letter, CV and contact information for 3 references should be sent to:
For primary consideration apply by November 28, 2018
Positions will remain open until filled.
The University is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service as appropriate to this position.
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
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