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Computational Economist - TERM

Argonne National Laboratory
Lemont - United States
S: Competitive

Position Description

Develop and apply economic models, both analytical and numerical, on problems related to ecosystem services, climate change, and energy-environment interactions. Investigate how agent-based modeling and/or dynamic optimization techniques can be used to better understand natural resource systems. Apply innovative modeling systems, including input-output schemes, to assess regional and state natural resource economic issues. Work closely with ecologists and physical scientists in a multidisciplinary environment. Produce technical reports and publications of findings and results. This position is part-time.

Position Requirements

Considerable skill in developing and applying analytical and numerical modeling schemes, including agent-based and dynamic optimization computations to natural resource systems.
Considerable skill in applying innovative modeling systems, including input-output methods to investigate regional and state natural resource economic issues.
Considerable knowledge of natural resource economic theory and applied regional analysis.
Considerable skill in written and oral communications.
Good knowledge of macroeconomics (growth and development).
Good skill in interacting effectively with scientific and engineering professionals.
Good skill in meeting project deadlines and staying within budgetary limits.
Good skill in working on several projects simultaneously.
Must demonstrate excellent career growth potential, including proposal development.Knowledge of ecological systems and ecosystem services as these relate to economic conditions and sustainability; understanding of climate issues and adaptations to climate change; and knowledge of economic considerations in land use planning activities are preferred.

Job summary

Employer:

Argonne National Laboratory

Location:

Lemont, United States

Education:

PhD/Doctorate

Sector:

Economist

Salary:

Competitive

Job Type:

Permanent

Hours:

Full-Time

Posted:

27th May 2016

Apply By:

25th June 2016

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