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Machine Learning Postdoc Jobs in Pennsylvania (NOW HIRING)

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 ...

POSITION SPECIFICS Postdoctoral Scholar (Machine Learning or Artificial Intelligence in Molecular and Cellular Biology) The National Synthesis Center for Emergence in the Molecular and Cellular ...

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 ...

Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks for ... Responsibilities The postdoctoral scholar will be expected to: * Conduct original research in ...

... 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 ...

A postdoctoral scholar position is available in the Computational Electromagnetics and Antennas ... using Machine Learning based multi-physics tools for predictive modeling, high-dimensional ...

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Machine Learning Postdoc information

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:
Infographic showing various Machine Learning Postdoc job openings in Pennsylvania as of July 2026, with employment types broken down into 1% As Needed, 68% Full Time, 26% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.
Postdoctoral Scholar

Postdoctoral Scholar

Penn State University

University Park, PA • On-site

Full-time

Posted 29 days ago


Penn State University rating

7.8

Company rating: 7.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

197th of 544 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
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 State University is seeking applications for a Postdoctoral Researcher position in the field of computational land surface hydrology, with a focus on Foundation AI model pretraining and finetuning, geospatial data processing and physics-informed machine learning. Prior experiences with these topics are highly desired. Pending approval of the grant, the successful candidate will work on innovative research in hydrology, collaborating with Dr. Shen and other faculty members, while also participating in the development of research projects and providing support to graduate students.
The postdoctoral scholar will combine foundation AI modeling and differentiable modeling (a genre of physics-informed machine learning) for hydrologic modeling to improve large-scale hydrologic forecast. The scholar will work with a large, interdisciplinary team on the next-generation land surface model. Especially, the scholar will integrate state-of-the-art AI and physics-informed AI techniques into an operational system. The contribution could bring benefits to society and reduce the damage of floods.
Duties include, but are not limited to:
  • Develop and implement novel modeling techniques.
  • Stay current with the latest developments and be willing to learn and adopt frontier methods.
  • Collaborate with research team members to design, execute, and interpret research findings.
  • Contribute to the development of high-quality research publications and presentations.
  • Provide support to graduate students within the department.

Requirements:
The Postdoctoral Researcher should possess a Ph.D. in hydrology, civil engineering, environmental science, or a closely related field by the appointment start date.
The successful candidate will also have:
  • A strong background in numerical modeling and the application of computational methods to land surface hydrological problems.
  • Research experience with a track record of published work in relevant scientific journals.
  • Excellent communication, teamwork, and problem-solving skills.
  • Proficiency in programming languages, such as Python or Fortran.
  • Experiences with machine learning is a plus to the application.
  • Solid understanding of the physical hydrologic cycle and large-scale geographic datasets.

The Pennsylvania State University offers a dynamic research environment, providing access to world-class facilities and resources. We encourage highly motivated candidates with a passion for advancing the field of computational hydrology to apply for this exciting position. To apply, please submit your CV, a cover letter detailing your research interests and experience, and contact information for three references with your online application.
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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