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The Courant Institute at New York University (NYU) is seeking expression of interest from a highly motivated Postdoctoral Associate to join our team working on improving the representation of sub-grid scale physics for climate models. This effort is part of the Learning Earth with Artificial Intelligence and Physics (LEAP), an NSF-funded Science and Technology Center. The scientific goal of this project is to enhance climate projections by reducing errors in climate models, specifically those rooted in the representation of the atmospheric boundary layer, using machine learning (ML).

Working directly with Professor Sara Shamekh (NYU), the successful candidate will also collaborate with Pierre Gentine (Columbia University) and with a team of interdisciplinary researchers, to develop and implement ML techniques for climate phenomena that span multiple scales and aspects of physics. This includes a focus on non-local boundary layer turbulence and shallow clouds.

This full-time appointment is available immediately. It is initially for one year, with the possibility of renewal for up to three years, subject to satisfactory performance and available funding.

In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is $62,500 - $70,000. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.

Required 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-paced environment

For full consideration, applicants should submit via Interfolio, the following by June 30th, 2024:

+ a Curriculum Vitae with a list of publications,

+ a cover letter (no more than 2 pages) detailing your research experience, available start date, career plans, and how your interests would fit the project.

+ 3 confidential letters of recommendation.

For additional information, please contact Sara Shamekh ([email protected])

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