Postdoctoral researchers in Climate Physics and Machine Learning at NYU

New York University

Description

The Center for Data Science (CDS) and the Courant Institute at New York University (NYU) seek a highly motivated postdoctoral fellow to join our team working on foundational models for multiscale multiphysics for climate models, as part of the international project, M2LInES https://m2lines.github.io. The scientific goal of this project is to improve climate predictions by reducing climate model errors at the air-sea/ice interface using machine learning (ML). 

The successful candidate will work with Profs Sara Shamekh and Laure Zanna, and with a team of interdisciplinary researchers to develop and implement ML for climate phenomena that span multiple scales and physics, in particular non-local boundary layer turbulence. 

The position, available immediately, is a full-time appointment, initially for one year, with the possibility of renewal for up to 3 years, subject to satisfactory performance and available funding.

In compliance with NYU's Pay Transparency Act, the annual base salary range for this position is $62,500 - $94,000. NYU considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer quality, as well as market and organization considerations. 

Qualifications

  • Completion of a PhD in physics, mathematics, computer science, engineering, statistics, or a related field at the time of the appointment;
  • Strong programming experience;
  • Strong interest in the application of machine learning to science and engineering problems;
  • A record of relevant publications in the peer-reviewed scientific literature appropriate to their career stage; 
  • Ability to work independently and as part of an interdisciplinary team. 
  • Ability to work in a fast pace environment 
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Confirmed an hour ago. Posted 30+ days ago.

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