[ES_JOBS_NET] Postdoctoral Research Associate - Heat and Health Applications of Statistical Downscaling, Princeton, NJ

[Anna P. Valerio]

Princeton University’s Atmospheric and Oceanic (AOS) Sciences Program, in cooperation with NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL), the National Integrated Heat Health Information System (NIHHIS) [heat.gov<http://heat.gov>], and the NOAA/NESDIS/National Centers for Environmental Information (NCEI) Regional Climate Services Program-Eastern Region, seeks applications for a postdoctoral or more senior research scientist to conduct research to advance the development and delivery of place-based climate information products and services that help NOAA’s health sector stakeholders (e.g., public health agencies, epidemiologists) make science-informed decisions.

The health impacts of rising temperatures in a changing climate are expected to be many, including greater incidence of heat-related illnesses, water- and vector-borne diseases, reduced food security, and mental health impacts (National Climate Assessment, 2018)[1]<applewebdata://BE71A9A8-6CA9-4AC2-9873-C201BFF79046#_ftn1>. This opportunity seeks applicants with a strong interest in the application of climate science and CMIP6 climate model output to understand these impacts and potential solutions. Candidates who have, and are interested in further developing, skills in applying actionable science that transfers knowledge gained from climate models to applied researchers and decision makers are encouraged to apply. A Ph.D. in physical geography, statistics/biostatistics, environmental, climate, atmospheric, physical sciences is required. Candidates should be skilled in the application of statistical methods, including uncertainty analysis, and be familiar with North American climate and the application of climate science to practitioners. We expect the post-doc to engage regularly with governmental and non-governmental colleagues and stakeholders, and to co-produce climate model output aligned with health sector needs. Programming skills in R or Python are required, as are strong communication skills. Other beneficial experiences include prior work with downscaled multi-decadal climate projections and/or machine learning methods, and interdisciplinary experience bridging climate science with public health or other policy-relevant applications. This is a full-time, term-limited position for one year with the possibility of renewal subject to performance and available funding, for a maximum of three years.
This position is based at NOAA GFDL/Princeton University. The successful candidate’s project will be primarily coordinated with GFDL’s Statistical Downscaling team, with continuous interdisciplinary dialog among colleagues. Project specifics will be determined by the candidate’s experience and alignment of project goals with NOAA priorities. For additional information on potential projects and the project team, visit www.gfdl.noaa.gov/heat-and-health-downscaling<http://www.gfdl.noaa.gov/heat-and-health-downscaling> or contact Keith Dixon (keith.dixon at noaa.gov<mailto:keith.dixon at noaa.gov>), Ellen Mecray (Ellen.L.Mecray at noaa.gov<mailto:Ellen.L.Mecray at noaa.gov>) and Hunter Jones (hunter.jones at noaa.gov<mailto:hunter.jones at noaa.gov>).

Applicants should apply online at https://www.princeton.edu/acad-positions/position/31521. Complete applications include a cover letter, CV, publication list, and 3 letters of recommendation. Applications should be accompanied by a statement of research interests outlining the candidate’s vision for a research topic using statistically downscaled climate projections to respond to the needs of the heat and human health sector, including the assessment and communication of uncertainties across disciplines. Application deadline is October 15, 2023, 11:59 pm EST. Review of applications will begin immediately and continue until the position is filled. Princeton is interested in candidates who, through their research, will contribute to the diversity and excellence of the academic community.
This position is subject to Princeton University's background check policy.
Princeton University is an equal opportunity/affirmative action employer, and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.

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[1]<applewebdata://BE71A9A8-6CA9-4AC2-9873-C201BFF79046#_ftnref1> USGCRP, 2018: Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, 1515 pp. doi: 10.7930/NCA4.2018.
Anna Valerio :8)
Princeton University
AOS Program
300 Forrestal Road, 209 Sayre Hall
Princeton, NJ 08540
phone:  609-258-6677
fax: 609-258-2850
e-mail:  apval at princeton.edu<mailto:apval at princeton.edu>



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