*Earth Systems Modeling Postdoctoral positions (three)*
*Position Information* Position Title: Post-Doctoral Associate Requisition Number: 192697 Starting Pay Rate: Dependent on qualifications Department Name: Forest Resources College: Food, Agricultural and Natural Resource Sciences Job Open Date: 07-18-2014 Job Close Date: Open until filled *Required/Preferred Qualifications * Required qualifications: Ph.D. in ecosystem ecology, ecophysiology, ecosystem physiology, biogeochemistry, computer science, systems modeling, or other relevant fields. *Duties/Responsibilities * We are seeking applications for three post-doctoral associates at the University of Minnesota for a DOE-supported project in Earth systems modeling. The applicants will work with Drs. Peter Reich (Department of Forest Resources, U of Minnesota), Peter Thornton (Oak Ridge National Laboratory), Arindam Banerjee (Department of Computer Science, U of Minnesota), Jens Kattge (Max Planck Institute for Biogeochemistry), and Owen Atkin (Australian National University). The appointments have available funds for three years, with appointments initially for one year with potential for renewal depending on performance. Start dates: October 1 or as soon thereafter as possible. This project will advance global land models by shifting from the current plant functional typePFT approach to one that better utilizes the variability of plant traits, including how they vary with key drivers such as temperature, moisture, and atmospheric CO2. Land surface models have developed to include mechanistic representations of vegetation physiology, C and nutrient dynamics in plants and soils, how they respond to changing climate and chemistry, and how those changes might feedback to influence changes in atmospheric greenhouse gases themselves. Our work will address these processes. The trait-based approach will improve land modeling by: (1) incorporating global biogeographical patterns and heterogeneity of traits into model parameterization, thus evolving away from a framework that considers large areas of vegetation to have near identical trait values; (2) utilizing what is known about trait-trait, -soil, and -climate relations to improve algorithms used to predict processes at multiple stages; and (3) allowing for improved treatment of physiological responses to environment (such as temperature and/or CO2 response of photosynthesis or respiration). The work will focus on the CLM model, but may involve work with other models as well. The three postdocs will work together as part of a larger team, but will have different responsibilities. The expertise required and components each will be responsible for include: Position #1: Develop reliable methods of estimating continuous trait values for diverse vegetation types, species mixtures, climate zones, and climate conditions. Required expertise: applied math (e.g., for trait data assimilation and uncertainty analyses; parameter estimation; trait mapping). This postdoc will work most closely with Banerjee, Kattge, and Reich. Position #2: Develop an approach to incorporating trait data to replace PFT-based trait assignments, including how these traits vary with key drivers (e.g., temperature, moisture, and atmospheric CO2). Required expertise: plant physiology and ecosystem ecology; with quantitative skills to identify and interpret key traits, trait relationships, and other physiological and ecosystem processes, and to conceptually develop parameterization schemes and modified model algorithms. This postdoc will work most closely with Reich, Atkin, and Thornton. Position #3: Hands-on coding of CLM model, implementation of model runs (CLM), and evaluation of model output in relation to empirical data (e.g., flux data) or comparison model output. Required expertise: quantitative analysis of ecosystem dynamics, computer model development and application, experience working with large multi-dimensional datasets. This postdoc will work most closely with Thornton, Kattge, and Reich. *Application Instructions * Applicants must apply online at employment.umn.edu/applicants/Central?quickFind=122173. Applications must include a statement of research interests, a CV, and three letters of reference. Specific questions should be addressed to Dr. Peter Reich, pre...@umn.edu. Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment. As an institution committed to demonstrating excellence through diversity, the College of Food, Agricultural and Natural Resource Sciences is committed to hiring a diverse faculty and staff, and actively encourages candidates from historically underrepresented groups to apply.
