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Physics Informed Machine Learning Jobs in Pennsylvania

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 ...

The core objective of this research is to advance physics-informed machine learning architectures to process complex, real-world geodetic and acoustic datasets for subsurface energy applications. The ...

... physics-informed machine learning, and digital twins to enhance engineering evaluation and control of the subsurface during characterization, drilling, stimulation, and/or production will be ...

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Physics Informed Machine Learning information

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

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What cities in Pennsylvania are hiring for Physics Informed Machine Learning jobs? Cities in Pennsylvania with the most Physics Informed Machine Learning job openings:

Postdoctoral Scholar

Penn State University

University Park, PA • On-site

Full-time

Posted 17 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

178th of 539 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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