Guest Faculty Research Participant - Peng Chen

Argonne National Laboratory • Lemont, IL

7d

About The Position

The proposed research focuses on advancing scientific machine learning techniques for geoscience applications, particularly in flood prediction by leveraging physics-informed machine learning methods. We will explore two innovative architectures based on our recent developments: a latent attention neural operator, which efficiently captures temporal correlations in complex dynamical systems, and the latent dynamics network, which integrates conditional physics-informed neural networks (PINNs) to enhance accuracy and generalizability. These methodologies have demonstrated success in modeling complex dynamical systems including nonlinear diffusion reaction equations, Navier—Stokes equations, and shallow water equations, and will be further adapted to improve predictive capabilities for flood events in the Midwest region, covering northern Illinois, southern Wisconsin, and western Iowa. The study will use shallow water equations as the physical model and leverage physics-based flood simulation results as training data, with the goal of developing a efficient, robust, physics-informed, and data-driven model for flood prediction in supporting energy utility planning. This research aims to ridge physics-based modeling with machine learning approaches, addressing practical challenges in real-world geoscience applications. Position Requirements Job Family Visiting Faculty Appointment Job Profile Guest Faculty Research Participant Worker Type Faculty Time Type Part time As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law. Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department. All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment. Interested in translating science into innovation? Build your career at Argonne. At Argonne, we view the world from a different perspective. Our scientists and engineers conduct world-class research in clean energy, the environment, technology, national security and more. We’re finding creative ways to prepare the world for a better future. To learn more about Argonne's benefits programs, amenities, and other employee programs, visit our main Careers site. To learn more about the exciting science going on at Argonne, visit our Science and Technology page. To request a reasonable accommodation or for other application support, contact us anytime at [email protected] or 630-252-2336.

What This Job Offers

• Job Type: Part-time
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees