We are seeking a full-time Assistant Research Scientist to join a frontier research collaboration developing next-generation AI methods for scientific applications, particularly physics and climate, at the NYU Courant Institute School of Mathematics, Computing, and Data Science.
The successful candidate will contribute to building and evaluating physics-constrained AI foundation models for climate predictions, including generalization to unseen climate forcings, and extreme events. The candidate will be primarily advised by Prof. Laure Zanna and co-advised by Prof. Carlos Fernandez-Granda, as part of the M2LInES collaboration They will also have the opportunity to collaborate with leading scientists in the field, which in addition to M2LInES scientists, include Jesse Rusak and Alex Merose from Open Athena, Ai2 Climate Modeling, and Prof. Richard Turner (Cambridge), on creating a new generation of AI foundation and world models for Climate.
This will build on a suite of major developments led by the team in developing AI emulators for the ocean, sea-ice, and atmosphere, and the full climate science system, with 1000x speedups over the original models. The expansion of these works includes exploring multiple resolutions, multimodality, and the grand challenges of learning physics on multi-century timescales for climate projections.
The position, available immediately, is a full-time appointment, initially for one year, with the possibility of renewal for two additional years, subject to satisfactory performance and available funding.
Some examples of recent work (more at M2LInES):
Multi-resolution ocean AI model, Samudra 2: https://doi.org/10.1029/2025GL119340
Coupled ocean-atmosphere AI model, SamudrACE: https://doi.org/10.48550/arXiv.2606.02610
A conservative sea-ice AI model, FloeNet: https://doi.org/10.1029/2026GL122981
In compliance with NYU's Pay Transparency Act, the annual base salary range for this position is $58,656 - $110,000. 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. Candidates with particularly relevant or specialized knowledge may be considered for compensation above the higher end of the range.
Education: Bachelor's degree in computer science, machine learning, applied mathematics, engineering, physical science, or a related technical discipline. Master's degree is a plus.
2+ years of research experience
Expertise or strong demonstrated skill in deep learning and computational science
Experience or interest in developing methods for scientific applications (not necessarily climate-related)
Proficiency in Python
Experience with HPC (GPUs preferred) is a plus
Experience with agentic programming is a plus
Related Skills and Other Requirements:
Ability to work at the interface of AI and science/engineering problems
Ability to contribute to multiple projects in a fast-paced environment
Ability to work both independently and collaboratively as part of an interdisciplinary team
Outstanding written and oral communication skills
Technical and scientific curiosity
A record of relevant projects, publications, or software appropriate to their career stage
For full consideration, applicants should submit via Interfolio, the following by September 20th 2026 (earlier applications are strongly encouraged):
A cover letter (no more than 2 pages) detailing 1) research/technical experience, 2) how you would fit our project, and 3) available start date.
A Curriculum Vitae (no more than 2 pages)
A list of relevant projects, publications, and/or software repositories (including GitHub repos)
2 confidential letters of recommendation
Applications are reviewed only if you have fulfilled the requirements above, and submitted to Interfolio.
For additional information, please contact m2lines@nyu.edu.
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NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.
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