New

Post Doctoral Scholar - AI and Machine Learning

The Pennsylvania State University
remote work
United States, Pennsylvania, University Park
201 Old Main (Show on map)
Mar 03, 2026
APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday. CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday. If you are NOT a current employee or student, please click "Apply" and complete the application process for external applicants. Approval of remote and hybrid work is not guaranteed regardless of work location.For additional information on remote work at Penn State, seeNotice to Out of State Applicants. This is a term position; length of the term will be discussed during the interview process. Continuation past the termlengthdiscussed willbebasedonuniversityneed,performance,and/oravailabilityoffunding. POSITION SPECIFICS The Department of Meteorology and Atmospheric Science and Institute for Computational and Data Sciences (ICDS) at Penn State is seeking a postdoctoral scholar in the area of artificial intelligence (AI) and machine learning (ML) applied to numerical weather prediction and data assimilation. In particular, the postdoc would be part of the team spanning NASA Goddard, Purdue University, Penn State University, and others to support the project "Machine-Learning to Improve Cycling and Forecasts with GEOS and Expedite the Evaluation of Assimilating Observations from New Instruments," supported by the NASA AIST program. The project involves the training, tuning, and evaluation of computer vision based ML surrogate models for the atmosphere and sea surface as part of the ensemble component of the NASA GEOS hybrid ensemble data assimilation system. Evaluations based on principles from machine learning, data assimilation, predictability, and atmospheric and oceanic phenomena on high performance computing (HPC) environments will be important for the project. Explorations of additional ways to hybridize data assimilation and machine learning are possible. The postdoc would join a cohort of AI/HPC postdocs affiliated with ICDS, which would provide opportunities to engage in an interdisciplinary community and interact with the different faculty co-hires and researchers in the institute applying these techniques to various disciplines. Required Qualifications A Ph.D. in a discipline related to this work, including Meteorology and Atmospheric Science, Computer Science, Engineering, Mathematics, Statistics is required by the start date. Must provide proof of a scheduled dissertation defense date for a PhD by the time ofoffer. Strong computer programming skills and the ability to work independently on complex problems. Expertise in applying and evaluating data assimilation and/or machine learning techniques. Ability to work effectively as part of a team, with strong written and oral communication skills, and motivation and ability to meet project timelines. Preferred Qualifications Previous experience training and evaluating deep learning emulators for high dimensional geophysical systems. Previous experience using ensemble and hybrid variational data assimilation systems. Expertise with the predictability of atmospheric and earth system predictions. Preferred Start Date: June 1, 2026 The position would be for one year, with the possibility of renewal for a second year pending good performance and availability of funds. Application Instructions Interested candidates should submit a cover letter describing their interest in the position, a CV, and names & contact information of up to three references. Questions regarding the position may be directed to Dr. Steven Greybush, sjg213@psu.edu. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s) in accordance with University policies. BENEFITS Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being. For more detailed information, please visit ourBenefits Page. (Note: For Postdoctoral benefits, please see our Postdoctoral Benefits page.) CAMPUS SECURITY CRIME STATISTICS Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here. EEO IS THE LAW Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473. Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university's teaching, research, and service mission. 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