[ES_JOBS_NET] Integration Software Engineer Opportunity - Columbia University

[Aileen Goldberg]

Position Summary

The recently awarded 2021 National Science Foundation Science and 
Technology Center Learning the Earth with Artificial Intelligence and 
Physics (LEAP,*_https://leap.columbia.edu/_*) aims to develop 
next-generation climate models by developing and applying modern data 
science algorithms. /LEAP is a joint effort between Columbia University, 
the University of California Irvine, New York University, The University 
of Minnesota, Teachers College, the National Center for Academic 
Research (NCAR), and the NASA Goddard Institute for Space Studies 
(GISS). / LEAP’s primary research objective is to improve near-term 
climate projections by merging Earth System modeling with new methods in 
machine learning.

The Integration Software Engineer (open rank) will work with a team of 
scientists from the LEAP center and NCAR and with NCAR software 
engineers to support the development of machine learning algorithms and 
their implementation and testing in the Community Earth System Model (CESM).

Though this position will be hired through the LEAP project by Columbia 
University, it is expected that the applicant will work within the CESM 
Software Engineering Group (CSEG) in the Climate and Global Dynamics 
Laboratory (CGD), which is part of the National Center for Atmospheric 
Research (NCAR), located  in Boulder, Colorado.

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Responsibilities

  * Provide software engineering support to aid implementation of new
    machine-learning based science, maintenance of testing frameworks,
    and development of new machine learning infrastructure in the CESM.
  * Contribute code changes and upgrades in support of CESM and LEAP
    community development activities and science goals.
  * Develop, implement, test, analyze, and document the integration of
    machine learning methods in the CESM.
  * Write code and assist in the design of system software for these
    systems.

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Minimum Qualifications

  * Bachelor’s degree in computer science or physical science or its
    equivalent required.
  * A minimum of 4-6 years of related experience required in software
    development or climate / Earth System Modeling experience.
  * Some experience with machine learning.
  * Excellent interpersonal and oral and written communication skills
    required.
  * Must be skilled at developing strong relationships with both
    internal and external partners.

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Preferred Qualifications

  * Demonstrated experience in supercomputing programming environments
    including MPI, OpenMP, NetCDF.
  * Demonstrated ability to debug complex software running on hundreds
    to thousands of processors.
  * Demonstrated skill in the use of git and GitHub for source code
    management.
  * Advanced knowledge of modern Fortran, Python, and shell.
  * Advanced ability to work in a UNIX environment.
  * Coursework or experience in undergraduate-level physics or
    environmental sciences.
  * Facility with calculus, differential equations, linear algebra,
    machine learning, and statistics.
  * Experience in plotting and visualizing scientific data, or
    experience with graphical analysis tools.
  * Experience in numerical (weather/climate) model development and
    operation.
  * Proven ability to plan as well as coordinate development work and
    meet deliverable deadlines.
  * Ability to convey advanced technical concepts to others, including
    aptitude for public speaking to scientific, technical,
    customer/sponsor, and public audiences.
  * Excellent oral and written communication skills.
  * Demonstrated ability to work as part of a diverse, collaborative,
    multi-institution team.

Apply to link:

https://opportunities.columbia.edu/en-us/job/525685/integration-engineer




-- 
*Aileen Goldberg*(she/her)
/Talent Manager
/
THE CLIMATE SCHOOL | COLUMBIA UNIVERSITY
Lamont-Doherty Earth Observatory
O: 845.365.8357 | C: 917.991.5925
www.climate.columbia.edu <https://www.climate.columbia.edu>
www.lamont.columbia.edu <https://lamont.columbia.edu>
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