Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
  • This site is mobile friendly. You do not need a log-in or password to access information.
  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
  • The site is refreshed daily to remove out-of-date content.
  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.

Job Information

New York University [EOI] Postdoctoral Associate - Learning Earth with Artificial Intelligence and Physics (LEAP) in New York, New York

The Courant Institute at New York University (NYU) is seeking expression of interest from a highly motivated Postdoctoral Associate to join our team working on improving the representation of sub-grid scale physics for climate models. This effort is part of the Learning Earth with Artificial Intelligence and Physics (LEAP), an NSF-funded Science and Technology Center. The scientific goal of this project is to enhance climate projections by reducing errors in climate models, specifically those rooted in the representation of the atmospheric boundary layer, using machine learning (ML).

Working directly with Professor Sara Shamekh (NYU), the successful candidate will also collaborate with Pierre Gentine (Columbia University) and with a team of interdisciplinary researchers, to develop and implement ML techniques for climate phenomena that span multiple scales and aspects of physics. This includes a focus on non-local boundary layer turbulence and shallow clouds.

This full-time appointment is available immediately. 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 - $70,000. 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.

Required 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

For full consideration, applicants should submit via Interfolio, the following by June 30th, 2024:

  • 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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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. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels.

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