Columbia University's Data Science Institute and Lamont-Doherty Earth Observatory seek a postdoctoral investigator interested in studying oceanic sub-mesoscale processes and the spatial heterogeneity of marine phytoplankton visible in satellite imagery. This cross-disciplinary research project will apply Bayesian machine learning techniques to satellite observations in order to infer unknown physical and ecosystem parameters, with the goal of improving understanding of submesoscale physics and biology. The position will be jointly supervised by Profs. Joaquim Goes (Biological Oceanography), Ryan Abernathey (Physical Oceanography), and Tony Jebara (Computer Science).
Candidates with knowledge in one or more areas that include fluid dynamics and numerical modeling, coupled physical-biological oceanographic processes, remote sensing and machine learning will be preferred. The position is initially for a year but extendable by a year depending on performance. The candidate should be highly motivated and have demonstrated ability to work independently and a willingness to work across disciplinary boundaries. Programming skills in Matlab, Python etc., and strong oral and written communication skills are essential. For more information about this position, contact Joaquim Goes (firstname.lastname@example.org), Ryan Abernathy (email@example.com) and Tony Jebara (firstname.lastname@example.org).
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