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
- 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. Qualifications- 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
Application Instructions 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.
