Oliver Fringer at Stanford University and collaborators at the San Francisco Estuary Institute
(SFEI) and the US Geological Survey (USGS) seek a postdoc to work on the development of a
harmful algal bloom (HAB) prediction system using machine learning to synthesize a
combination of data from numeral models, in-situ measurements, and satellite remote sensing of
San Francisco Bay (SF Bay). The focus is on machine learning given that circulation +
biogeochemical models have difficulty predicting the occurrence of HABs in such systems. We
hope to develop a practical model that can be used by stakeholders concerned with how nutrient
inputs affect HABs and water quality in SF Bay. The position will be based in the Oceans
Department at Stanford and there will be extensive collaboration with partners at SFEI and
Applicants must have a Ph.D. from an accredited university and a publishing record in peerreviewed
journals. The ideal candidate would be an expert in machine learning applied to some
aspect of physical oceanography and/or ocean biogeochemistry. Applicants without expertise in
machine learning must have expertise in modeling of estuarine physics and/or biogeochemistry
and must have some familiarity with Python and machine learning either through coursework or
research. Strong written and oral communication skills are essential.
To apply, please send a cover letter, cv, a sample publication, and a list of three references to
Oliver Fringer (email@example.com). Applications will be considered until the position is filled
(please check the status at web.stanford.edu/~fringer/postdoc.html). Ideally, the candidate could
start on 9/1/23, although later start dates will be considered. Please indicate your anticipated start
date in the cover letter and include “Postdoc in ML for HAB prediction” in the subject line.
The appointment will be for a maximum of 18 months (1.5 years), with an initial appointment of
12 months followed by a 6-month renewal, subject to performance. The 12-month salary for the
first year will be $70,740.
Stanford is an equal opportunity employer, and all qualified applicants will receive consideration
without regard to race, color, religion, sex, sexual orientation, gender identity, national origin,
disability, veteran status, or any other characteristic protected by law.
- Job Type: Post-doc
- Organization: Stanford University
- Qualifications: Required Qualifications: • Ph.D. from an accredited university • Publishing record in peer-reviewed journals • Experience with Python programming • Expertise in machine learning applied to ocean physics/biogeochemistry -OR- in modeling of estuarine physics and/or biogeochemistry • Ability to work independently and collaborate effectively in an interdisciplinary environment • Strong written and oral communication skills
- How to apply: To apply, please send a cover letter, cv, a sample publication, and a list of three references to Oliver Fringer (firstname.lastname@example.org). Please indicate your anticipated start date in the cover letter and include "Postdoc in ML for HAB prediction" in the subject line.
- Location: San Francisco
- Web address: https://web.stanford.edu/~fringer/postdoc.html