[ES_JOBS_NET] Associate Research Scientist position in Atmospheric Modeling and Machine Learning, Columbia University, New York, NY

[Gregory Elsaesser]

Columbia University, Associate Research Scientist in Atmospheric Modeling
and Machine Learning
Apply at: apply.interfolio.com/140102

Columbia Engineering, the Fu Foundation School of Engineering and Applied
Science at Columbia University in the City of New York invites applications
for an Associate Research Scientist in the field of global atmospheric
modeling and machine learning, under the supervision of Greg Elsaesser at
Columbia University/NASA GISS and Brian Medeiros at NSF NCAR (National
Center for Atmospheric Research). The position is part of the National
Science Foundation-funded Learning the Earth with Artificial intelligence
and Physics <https://leap.columbia.edu/> (LEAP) Science and Technology
Center (STC), a multi-institutional center effort meant to improve climate
projections using novel artificial intelligence for better climate
adaptation.

The goal of this project is to build key connections that enable results
from machine learning activities developed within LEAP to be incorporated
and evaluated in the atmospheric component of the Community Earth System
Model (CESM). This work is expected to proceed in two parallel efforts that
will be coordinated by the incumbent. The first builds on ongoing work and
focuses on conducting and analyzing perturbed physics ensembles with the
Community Atmosphere Model (CAM) to quantify sensitivity of the simulated
climate to parameter choices. Machine learning approaches will be applied
to provide actionable information about parameter sensitivity and
optimization for specific climatic targets. By applying parameter
estimation techniques within the development version of CAM, this project
will inform model development in real time. This ARS will work with LEAP
and NCAR scientists to build the workflows that allow for rapid production,
analysis, and emulation of PPEs and to disseminate findings to CESM
developers and the wider research community. The second, equally important,
aim of the project is to establish more general support and coordination of
LEAP-developed machine learning activities, including conducting and
analyzing experiments using ML-based parameterizations and emulators as
well as explorations of methods to generate high-quality training data sets
for additional ML-based schemes.

The ARS will closely collaborate with members of the Atmospheric Modeling
and Predictability Section in the Climate and Global Dynamics Laboratory at
NCAR as well as with graduate students, postdocs, and other staff within
LEAP.

The applicant should have a background in atmospheric modeling, atmospheric
science, or closely related fields, and ideally should have significant
experience in machine learning or statistics.

One of LEAP’s goals is to increase the diversity in climate science and
data science. We welcome and encourage applications from individuals of all
backgrounds and identities. We are committed to building a diverse and
inclusive community and believe that a variety of perspectives and
experiences is essential to advancing our research and mission.
Qualifications

   - A Ph.D. in Atmospheric Science, Data Science, Computer Science,
   Physics, Earth System Science or a directly related discipline is required
   by the start of the appointment.
   - Strong programming skills are a requirement.

Preferred Qualifications

   - Post-doctoral experience and demonstrated experience in Earth System
   Science, Data Science, or similar.
   - Fluency in Python.
   - Familiarity with Fortran.
   - Advanced experience in machine learning.
   - Demonstrated experience in statistical/mathematical analyses of model
   output and/or observational datasets.
   - Experience running and analyzing global climate simulations on high
   performance computing platforms
   - Excellent command of the English language (verbal and written) and
   strong communication skills are desired.

Application Information:

Applications must include: (a) curriculum vitae (b) statement of research
(optional) (c) names of at least three references who may be asked to
provide letters.

For information on how to apply for this position, please visit
apply.interfolio.com/140102.
EEO Statement

Columbia University is an Equal Opportunity Employer / Disability / Veteran
Pay Transparency Disclosure

Salary Range: $77,000 - $90,000.

The salary of the finalist selected for this role will be set based on a
variety of factors, including but not limited to departmental budgets,
qualifications, experience, education, licenses, specialty, and training.
The above hiring range represents the University’s good faith and
reasonable estimate of the range of possible compensation at the time of
posting.

Posted 2024-02-01. Open until filled.
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