Postdoctoral Scientist In Terrestrial Biosphere Modeling Of Dryland Ecosystems

Posting Details

Title Postdoctoral Scientist in Terrestrial Biosphere Modeling of Dryland Ecosystems

Appointment Status Non-Tenure Track Department IU Bloomington Geography Position Summary

Postdoctoral Scientist Position in Terrestrial Biosphere Modeling of Dryland Ecosystems at Indiana University-Bloomington

A postdoctoral scientist position is available in Dr. Natasha MacBean's group in the Department of Geography at Indiana University (IU) Bloomington on terrestrial biosphere model (TBM) development for dryland ecosystems. This postdoc is funded by a NASA Carbon Cycle Program grant. The postdoctoral researcher will be responsible for utilizing the wide range of field and remote sensing data and outputs of the project to test, optimize and develop the ORCHIDEE TBM to better represent dryland ecosystem functioning. Multiple opportunities exist for collaborations with other project members and collaborators at NASA Goddard, the USGS Southwest Biological Science Center, the University of Arizona, and at IU Bloomington. Applicants are required to have strong prior experience working with terrestrial biosphere models/land surface models/dynamic vegetation models as well as HPC systems. Further qualifications are listed below. Remote work within the US is possible (please enquire for more details). This position is offered for 3 years from spring 2022.

Salary: Commensurate with experience. Full benefits included.

Start date: Spring 2022.

Basic Qualifications

• PhD, by start of appointment, in geography, environmental science, earth science, biology, atmospheric science, computational science or a related field. • Knowledge of terrestrial biogeochemical cycles and land surface processes. • Strong publication record. • Extensive prior experience working with global scale terrestrial biosphere models or equivalent (land surface models, earth system models, dynamic vegetation models) is required. • Strong inter-personal, collaboration, teamwork and organizational skills. • Substantial programming experience (preferably with Python and FORTRAN) is required. • Proficiency in developing/maintaining large datasets and scientific codes for numerical simulation and analysis on Linus/Unix OS and high performance computing systems (HPC) is required. • Prior experience working with Bayesian data assimilation methods is welcome but not required.

Department Contact for Questions

nmacbean@iu.edu

Additional Qualifications Salary and Rank Special Instructions

Please submit a CV, cover letter, and 1 page statement of research experience

For Best Consideration Date 02/15/2022 Expected Start Date OAA # 22112-04

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