UC Davis: Postdoctoral position on sea level predictability and machine learning

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Maike Sonnewald

Sep 1, 2023, 6:30:52 PM9/1/23
to Climate Informatics News
Dear all, I have an open position for a postdoctoral associate in my group at the University of California, Davis. The focus is on sea level predictability and machine learning. I would be grateful if you could share it in your networks!

Postdoctoral position on sea level predictability and machine learning

The Computer Science department at the University of California (UC), Davis invites applications to research the physical ocean processes and their interactions that contribute to sea level variability on subseasonal to decadal timescales. We will apply and develop data mining and sparse data inference methodologies to sea-level data. The machine learning applied will be targeted at gaining new knowledge and harnessing a network’s potential as a universal function approximator to also learn more about emergent drivers of variability. The larger objective of this study is to improve predictions of sea level variability originating from a seasonal to multidecadal prediction system developed at GFDL (SPEAR), as well as general climate models, by providing Process Oriented Diagnostics (POD) to the MDTF framework. The PODs address both the initial value and model error components of sea level prediction uncertainty.   

The position reports to Professor Maike Sonnewald at UC Davis and will collaborate with Aparna Radhakrishnan at Princeton University, John Krasting, Modeling Systems Division, and selected HPC and Scientific staff at the NOAA Geophysical Fluid Dynamics Laboratory as well as Matt Newman at the NOAA Physical Sciences Laboratory. The appointment will be through the UC Davis Computer Science Department and compensated accordingly. The appointment is for one year and may be renewed up to three years pending satisfactory performance.

A Ph.D. is required in a related field, for example, oceanography, physics, data science, or computer science. Ideal applicants will have experience with some combination of:

  • Scientific computer programming and realistic general circulation models

  • Physical oceanography using models, theory, observations, or some combination 

  • Advanced statistics, supervised and unsupervised machine learning

Note that the position does not require expertise in all of the above. Strong academic writing and communication skills in English are required.

Salary is competitive and full employee benefits are offered following University guidelines and candidate experience. 

How to Apply

Applicants should submit a CV, contact information for three references, and a cover letter (2 pages max) describing their areas of expertise and interest (tips for unfamiliar candidates). A statement on commitment to diversity is optional. References may be contacted for the candidates who make the shortlist for this position. Apply by submitting the online form: https://tinyurl.com/ccogPostdoc

and send the CV, cover letter to: compClim...@gmail.com

Screening of applications will begin October 11th 2023 and continue until the position is filled. This position is subject to the University's background check policy. For questions contact sonn...@ucdavis.edu.

Commitment to Diversity

UC Davis ranks among the Forbes best employers for Women and Diversity overall. We believe that it is vital to cultivate an environment that fosters the success of diverse individuals and that diversity, equity, and inclusion are fundamental to the success of our education and research mission. This commitment to diversity informs our efforts in recruitment and hiring as we actively seek colleagues of exceptional ability who represent a broad range of viewpoints, experiences, and value systems, and who share UC Davis' dedication to excellence.

UC Davis 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.

Full link: https://docs.google.com/forms/d/e/1FAIpQLSd911Ovi26Cb1Y_VKKdTPH9xWa7ePPejppD5aN1rE4HXN03tA/viewform

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