[ES_JOBS_NET] Postdoc position, CPAESS-GFDL-NCAR

[Andrew Newman]

Dear all,

We have an open postdoctoral position based at NOAA-GFDL in Princeton NJ,
but a remote work option is available to be determined with the successful
candidate.  The successful candidate will perform quantitative
evaluation of downscaled datasets to improve our understanding of the
impacts of methodological choices on product performance to develop
actionable climate knowledge for climate adaptation and resilience.  The
successful candidate will work with a team across GFDL, NCAR, Cornell,
MITRE and interface with stakeholders within DoD.  See below for more
details and apply here!
<https://ucar.wd5.myworkdayjobs.com/en-US/UCAR_Careers/details/CPAESS-Postdoctoral-Researcher_REQ-2023-288-2>


*CPAESS Postdoctoral Researcher*
Job Description Summary:
UCAR is excited to announce the job opening for the CPAESS Postdoctoral
Researcher role working with NOAA's Geophysical Fluid Dynamics Laboratory
(GFDL). This position will quantitatively evaluate a large collection of
downscaled climate projection data products for the United States,
rigorously comparing them with observations and each other. This position
has a goal of developing actionable climate knowledge of use to applied
researchers and stakeholders interested in climate adaptation and
resiliency, the post-doc will develop methods and workflows to conduct
analyses, identify key data product characteristics, investigate the role
of downscaling methodological assumptions, and report results to an
interdisciplinary audience interested into what extent the downscaled data
products are fit for purpose for their applications of interest.

Position Details:

Visa Sponsored Job:
No

Relocation Assistance Eligible:
No

Job Location:
Princeton, New Jersey

Position Type & Term:
Full time, Term - 6 months or more (Fixed Term)

Compensation Min - Mid Range:
62,285.00 USD - 77,857.00 USD

**Final salary and rates are based on education, experience and skills
relevant to the role.**

Application Notes

Application Deadline:

   -

   This position will be posted until filled with priority given to
   applications submitted by Friday, September 1.

Required application materials: *(preferably in PDF Format)*

   -

   Resume
   -

   Cover Letter - Please address how your skills and experience meet the
   needs of this position (for more information, please refer to the Key
   Responsibilities and Knowledge, Skills, and Abilities sections of this job
   posting).

Background Checks: Conducted for candidates selected for hire. Learn more
<https://www.ucar.edu/opportunities/careers/faqs>.


Work Location: Princeton, NJ or Fully Remote

*Regardless of flexible work arrangements, UCAR requires ALL positions to
be performed within the U.S., excluding U.S. Territories.*

What You Will Do

Here is a brief summary of what one would expect to be generally
responsible for in this role.

Processing and Analysis of Downscaled Climate Data Products

   -

   Contribute to the end-to-end processing and analysis of a large set of
   downscaled climate projection data products.
   -

   Being drawn from several non-standardized sources, careful data
   processing into more consistent forms and quality control efforts will be
   required in preparation of conducting quantitative analyses of several
   commonly used U.S. surface climate variables (e.g., daily minimum and
   maximum temperature and precipitation).
   -

   Make use of existing analysis codes and develop new analysis programs to
   explore characteristics of downscaled physical climate variables, including
   the representation of extreme and compound events. These analysis efforts
   will entail close collaboration between the post-doc, the host GFDL
   researcher and others working on this multi-institutional  project.
   -

   Lead the development and publication of one or more peer-reviewed
   articles based on these analyses.

Exploring Diagnostic Variables Relevant to Select Sites and Applications

   -

   Investigate diagnostic metrics that use downscaled climate time series
   as input to generate quantities of specific interest for a set of locations
   and applications (e.g., infrastructure, human health, ecosystems), in
   coordination with project colleagues, and informed by dialogues with select
   project stakeholders.
   -

   Develop codes to analyze the sensitivity of these diagnostic variables
   to the choice of downscaling method and greenhouse gas emissions scenario.
   -

   Provide documentation of code and communicate results in both technical
   forms and versions suitable for stakeholders.

Community and Stakeholder Engagement

   -

   Provide expertise to the scientific and stakeholder communities by
   attending virtually and/or in-person research workshops and conferences,
   giving presentations at conferences, seminars, and/or webinars, reviewing
   scientific manuscripts, and writing scientific journal articles.

Who We'd Love To Join Our Team

Successful candidates will ensure their application materials speak to the
following criteria:


Education and Experience

   -

   A Ph.D. or equivalent experience in atmospheric sciences or a related
   field;
   -

   Demonstrated understanding of statistical analyses as applied to climate
   projections and observations;
   -

   Research experience in a relevant field, with contributions to refereed
   journals.

Knowledge, Skills, and Abilities

   -

   Expertise working with large spatial climate and/or
   meteorological/weather data sets.
   -

   Expertise in one or more computing languages (such as Python or R) for
   statistical analysis, consistent data processing, and graphical
   presentation.
   -

   Strong skills in data analysis and statistical inference.
   -

   Demonstrated knowledge of U.S. regional climate and 21st century climate
   projections.
   -

   Strong written and oral communication skills, especially for scientific
   publications and presentations.
   -

   Ability to work both independently and collaboratively in a
   team-oriented environment.

*Desired, but not required: *

   -

   Familiarity with one or more bias correction, statistical downscaling,
   or dynamical downscaling methods.
   -

   Familiarity with CMIP6 climate model simulations, including their netCDF
   format data files.
   -

   Familiarity with netCDF Climate and Forecast (CF) metadata conventions.
   -

   Expertise in extreme value analysis as applied to weather or climate
   variables.
   -

   Expertise in writing modular analysis codes.
   -

   Expertise with version control software (such as Git or Subversion).




-- 
Andrew Newman, Ph.D. (he/him/his)
National Center for Atmospheric Research
P.O. Box 3000, Boulder, CO 80307-3000
http://staff.ucar.edu/users/anewman & Google Scholar Profile
<https://scholar.google.com/citations?hl=en&user=NIauackAAAAJ&view_op=list_works&gmla=AJsN-F6mUExXALoxUjaycWY6UbpD41blQpZqOxJCF-II5FyLCzp6Oydl6GhTCPYtiEMtl0GwjM2UkediCC0Mg3_c40BVEl2sqw>
ph: 303-497-8456, email: anewman at ucar.edu

*My working day may not be your working day. Please do not feel obligated
to reply to this email outside of your normal working hours.*
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