[EOI] Postdoctoral Researcher – Machine Learning for Climate Data Downscaling

Description

The Courant Institute of Mathematical Sciences at NYU is seeking expressions of interest from a highly motivated Postdoctoral researcher with expertise in machine learning and data science to join our team as part of the ACCLIMATISE project. This project aims to employ advanced machine learning methods to downscale climate data for high-resolution intervention planning, with a focus on public health applications across West Africa. ACCLIMATISE brings together experts from diverse fields, including machine learning, climate modeling, vector-borne disease modeling, and wireless technologies. The project is co-designed with research partners and  stakeholders from Senegal, Ethiopia, and Kenya to ensure our solutions are practical and impactful.

Project Overview

The successful candidate will develop machine learning models to downscale (super-resolution) large-scale climate model outputs to the sub-kilometer scale, enabling actionable insights for health-related interventions at the local scale. Advanced ML techniques, including generative models and probabilistic methods, will be essential in meeting these goals.

In addition, the project incorporates demographic, mobility, and gender data to build more robust, realistic models of climate-sensitive interventions, requiring innovative approaches for multi-modal data integration.

Key Responsibilities

• Develop and implement advanced ML algorithms, including generative models, for downscaling climate data.

• Work with large geospatial datasets and locally collected (single point) measurements.

• Collaborate with interdisciplinary teams from Europe and Africa and engage with stakeholders in Senegal, Ethiopia, and Kenya.

• Travel to West Africa once a year to attend annual meetings, work closely with local collaborators and ensure solutions meet regional needs.
  
  

This full-time appointment is available for a start date in December or January. 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 - $78,000. 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.

Qualifications

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

Application Instructions

Application Instructions

For full consideration, applicants should submit via Interfolio, the following by September 15th, 2025:

• 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 (ss18284@nyu.edu)

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