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Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via imaggeo.egu.eu)

Job advertisement Post Doc - Uncertainty characterization in the human-Earth system

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Post Doc - Uncertainty characterization in the human-Earth system

Position
Post Doc - Uncertainty characterization in the human-Earth system

Employer

PNNL

Homepage: https://www.pnnl.gov/


Location
College Park, Maryland, United States of America

Sector
Government

Relevant divisions
Biogeosciences (BG)
Climate: Past, Present & Future (CL)
Energy, Resources and the Environment (ERE)

Type
Full time

Level
Student / Graduate / Internship

Salary
Open

Required education
PhD

Application deadline
12 February 2022

Posted
25 January 2022

Job description

Job Description
Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, flexible work schedules and telework options. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Overview

The Joint Global Change Research Institute at Pacific Northwest National Laboratory is soliciting applications for a postdoctoral position advancing uncertainty characterization in the human-Earth system as part of the Global Change Intersectoral Modeling System (GCIMS) Science Focus Area. GCIMS focuses on improving the understanding of the complex interactions among energy, water, land, climate, socioeconomics, and other important human and natural systems at regional to global and seasonal to centennial scales. GCIMS has an emphasis on developing and applying an internally consistent, open-source, and computationally efficient modeling framework that captures the evolution of the integrated human–Earth system. The GCIMS project develops and uses the Global Change Analysis Model (GCAM) along with a suite of dedicated, open-source systems models that include Demeter (global land-use downscaling), Hector (climate emulator), Xanthos (global hydrology), fldgen (climate variability emulator), and Tethys (global water demand downscaling).

Responsibilities

The successful applicant will lead the analysis using the Global Change Analysis Model (GCAM; http://jgcri.github.io/gcam-doc/index.html) and related models (e.g., Hector, Xanthos). Specifically, this scientist will focus on generating and analyzing large ensembles of GCAM simulations that quantify the effect of changes in human and Earth system drivers on the energy, water, land system. The scientist is expected to use scenario discovery tools and possibly other machine learning techniques in this analysis. The scientist is expected to lead multiple peer-reviewed publications on this work; there will be many opportunities to work with the multi-disciplinary GCIMS team as well as collaborators in other national labs and universities.

Qualifications

Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.

Preferred Qualifications:

Preferred qualifications include the receipt of a PhD after January 1 2017; a background in engineering, physical sciences, applied mathematics, computational science, economics, hydrology, or related field; strong verbal and written communication skills; a willingness to work both independently and within a collaborative team environment, and a proven capability to publish in peer-reviewed journals. Previous graduate-level statistical coursework, as well as substantial programming experience, are required; experience with R or python is preferred but clear and well commented code in other languages is welcome.

Required information for application: A cover letter, CV, and individually-authored coding sample in R or Python. Applications that do not have all this requested information will not be considered. Please upload as one pdf file.

Hazardous Working Conditions/Environment

Not applicable

Additional Information

Not applicable

Testing Designated Position

Not applicable
Commitment to Excellence, Diversity, Equity, Inclusion, and Equal Employment Opportunity

Our laboratory is committed to a diverse and inclusive work environment dedicated to solving critical challenges in fundamental sciences, national security, and energy resiliency. We are proud to be an Equal Employment Opportunity and Affirmative Action employer. In support of this commitment, we encourage people of all racial/ethnic identities, women, veterans, and individuals with disabilities to apply for employment.

Pacific Northwest National Laboratory considers all applicants for employment without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at hr@pnnl.gov.

Drug Free Workplace

PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

Mandatory Requirements

Battelle requires employees to have a COVID-19 vaccine as a condition of employment, subject to accommodation. Applicants are required to disclose their vaccination status following a conditional offer of employment and must attest to being fully vaccinated with a Center for Disease Control (CDC)-approved COVID-19 vaccination, or provide documentation of need for medical or religious exemption from the COVID-19 vaccination requirement.