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Machine Learning Postdoc Jobs in Pennsylvania (NOW HIRING)

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 ...

... informed machine learning architectures to process complex, real-world geodetic and acoustic datasets for subsurface energy applications. The Postdoctoral Scholar will work primarily with Prof.

POSITION SPECIFICS Join a Dynamic Team Focused on Foundation AI modeling and Physics-Informed Machine Learning as a Postdoctoral Researcher at The Pennsylvania State University. The Pennsylvania ...

Prior background in machine learning, digital twins and electronic design automation is highly desired. The postdoc will have the opportunity to mentor graduate and undergraduate students. Guidance ...

... Postdoctoral Scholar to conduct research on projects in collaboration with Dr. Sanjay Srinivasan ... machine learning and multipoint geostatistics for characterization of fractures and novel ...

... a Postdoctoral Scholar beginning August 2026. The successful candidate will work with Professor ... Qualified candidates are expected to have a background in scientific machine learning,numerical ...

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What are the key skills and qualifications needed to thrive in the Machine Learning Postdoc position, and why are they important?

To thrive as a Machine Learning Postdoc, you need a deep understanding of machine learning algorithms, statistical modeling, and research methodology, typically supported by a completed PhD in a related field. Proficiency with programming languages like Python or R, experience with ML libraries (e.g., TensorFlow or PyTorch), and familiarity with large-scale datasets and cloud computing platforms are important. Strong analytical thinking, effective communication, and the ability to collaborate across multidisciplinary teams are standout soft skills in this position. These qualifications ensure innovative research contributions, successful project execution, and effective dissemination of findings in both academic and applied settings.

What is a Machine Learning Postdoc job?

A Machine Learning Postdoc is a research-focused position typically held after earning a Ph.D. in a related field. It involves conducting advanced research in machine learning, developing new algorithms, and publishing in top-tier conferences and journals. Postdocs often collaborate with faculty, industry partners, and other researchers to advance the state of the art in AI. The role may include mentoring students and contributing to grant proposals. It serves as a bridge between doctoral studies and a long-term academic or industry research career.

What are the typical responsibilities and collaborative aspects of a Machine Learning Postdoc position?

A Machine Learning Postdoc typically conducts original research, develops and tests new algorithms, and contributes to academic publications or patent applications. Daily tasks often involve data analysis, model building, and experimentation using advanced computational tools. Collaboration is key in this role, as postdocs frequently work alongside faculty, graduate students, and external industry partners to advance research objectives. Additionally, they may mentor junior researchers or students, present at conferences, and participate in grant writing or project planning. This mix of independent research and team collaboration fosters both professional growth and impactful scientific advancements.

What are the most commonly searched types of Machine Learning Postdoc jobs in Pennsylvania? The most popular types of Machine Learning Postdoc jobs in Pennsylvania are:
What are popular job titles related to Machine Learning Postdoc jobs in Pennsylvania? For Machine Learning Postdoc jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Machine Learning Postdoc jobs in Pennsylvania look for? The top searched job categories for Machine Learning Postdoc jobs in Pennsylvania are:

Post Doctoral Scholar - AI and Machine Learning

Penn State University

University Park, PA • On-site

Full-time

Posted 10 days ago


Penn State University rating

7.9

Company rating: 7.9 out of 10

Based on 100 frontline employees who took The Breakroom Quiz

173rd of 535 rated colleges and universities


Job description

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, see Notice to Out of State Applicants.
This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.
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 of offer.
  • 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 our Benefits 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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