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<span lang="EN" style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">Princeton University, in association with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), seeks postdoctoral scientists or research scientists for research
and development activities focused on data science and engineering. <o:p></o:p></span></p>
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<span lang="EN" style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">The scientist will collaborate with Princeton and GFDL researchers to enhance, analyze and deliver high-resolution earth system model data, with an emphasis
on Seamless System for Prediction and EArth System Research (SPEAR) for seasonal to multidecadal prediction and projection. The project will emphasize elements such as stakeholder engagement, earth system model development, service delivery with an overarching
objective connecting science with society. This encompasses the development of infrastructure and processes for data standardization, data warehousing, quality assurance development and data analysis. A successful candidate will work closely in different
aspects of the quality assurance and data engineering pipeline, developing usable and innovative solutions to build a prototype of sustainable online tools and services that are relevant and useful to a broad range of stakeholders making decisions about the
future. The selected candidate will join a vigorous research group at Princeton University, working in close collaboration with Ms. Aparna Radhakrishnan and members of a founding group. They will also closely collaborate with representatives of the Seasonal-to-Decadal
Variability & Predictability Division, Technical Services and Modeling Systems Division. The selected candidate will have access to state-of-the-art numerical models and high-performance computing systems at Princeton and in NOAA, working alongside GFDL model
developers and software engineers to advance quality assurance and data dissemination capabilities for making high-resolution earth system model output available to a diverse audience. <o:p></o:p></span></p>
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<span lang="EN" style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">Candidates must have a PhD in computer science, environmental and physical sciences, or a closely related field. The following attributes are desirable: a)
excellent problem solver and self-starter b) passion for software and science c) strong open-source software development experience d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with
some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application development i) NetCDF and Zarr data models f) earth system model development. Experience with software development,
analysis and data management tools, such as Python, R, Jupyter, Linux, Globus, STAC, GitHub, containers is recommended. Familiarity with cloud technologies, databases and Pangeo ecosystems is a bonus. <o:p></o:p></span></p>
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<span lang="EN" style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance
and continued funding; those hired at more senior ranks may have multi-year appointments. Princeton is interested in candidates who, through their research, will contribute to the diversity and excellence of the academic community. Applicants should apply
online at</span><span lang="EN"> <a href="https://www.princeton.edu/acad-positions/position/36921" target="_blank" style="color: purple;"><span style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">https://www.princeton.edu/acad-positions/position/36921</span></a></span><span lang="EN" style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">. Complete
applications should include a cover letter, CV, publication and presentation list, 3 letters of recommendation, and a one-to-two page personal statement and/or a research statement. Review of applications will begin November 30, 2024<span style="color: red;"> </span>and
continue until the position is filled. For additional information, contact Aparna Radhakrishnan (</span><span lang="EN"><a href="mailto:aparna.radhakrishnan@princeton.edu" style="color: purple;"><span style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif; color: rgb(17, 85, 204);">aparna.radhakrishnan@princeton.edu</span></a></span><span lang="EN" style="font-size: 12pt; line-height: 18.4px; font-family: "Times New Roman", serif;">). <o:p></o:p></span></p>
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<a name="_gjdgxs"></a><span lang="EN" style="font-size: 12pt; font-family: "Times New Roman", serif;">The work location for this position is in-person on campus at Princeton University. This position is subject to the 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.<o:p></o:p></span></p>
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<span style="font-size: 14px;">Anna Valerio :8)</span><br>
<span style="font-size: 14px;"><i>Department & Graduate Administrator</i></span><br>
<font color="#ff9300" style="font-size: 14px;">Princeton University</font><br>
<span style="font-size: 14px;">AOS Program</span><br>
<span style="font-size: 14px;">300 Forrestal Road, 209 Sayre Hall</span><br>
<span style="font-size: 14px;">Princeton, NJ 08540</span><br>
<span style="font-size: 14px;">phone: 609-258-6677<br>
fax: 609-258-2850<br>
e-mail: apval@princeton.edu<br>
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