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Job advertisement Postdoc position in Machine Learning for Climate Extremes at NYU

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European Geosciences Union

Postdoc position in Machine Learning for Climate Extremes at NYU

Postdoc position in Machine Learning for Climate Extremes at NYU


New York University


Seattle, United States of America


Relevant divisions
Climate: Past, Present & Future (CL)
Ocean Sciences (OS)

Full time

Entry level


Required education

Application deadline
Open until the position is filled

15 September 2021

Job description

The Courant Institute and the Center for Data Science at NYU have an open postdoctoral position in scientific machine learning as part of a new multi-institution international project, M2LInES. The scientific goal of this project is to improve climate predictions by reducing climate model errors using interpretable machine learning.

The postdoc will work with Profs Joan Bruna, Carlos Fernandez-Granda and Laure Zanna on the development of generalizable deep learning algorithms, with a focus on extreme events and uncertainty quantification. Predicting rare events from noisy and sparse data is a fundamental open question both in machine learning and climate applications. The postdoc will explore state-of-the-art approaches with the ultimate goal of improving machine learning models for climate processes (e.g., clouds, ocean mixing). An example of the kind of problems we are investigating can be found in this recent paper.

The position, available immediately, is a full-time appointment with the possibility of renewal, subject to satisfactory performance. Full consideration will be given to applications completed by October 18, 2021. Applications received after this date will only be considered if the position has not yet been filled.


  • Completion of a PhD in physics, mathematics, computer science, engineering, statistics, or a related field at the time of the appointment;

  • Background and interest in statistics and/or machine learning;
  • Programming experience;
  • Strong interest in the application of machine learning to scientific applications;
  • 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.

How to apply

For full consideration, applicants should submit the following at this webpage

  • a Curriculum Vitae with a list of publications,
  • a cover letter (no more than 2 pages) detailing their research experience, how their interests would fit the project, career plans, and available start date,
  • Names of 3 referees willing to write a recommendation.