Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks

The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate vulnerabilities. The Postdoctoral Appointee will be responsible for the conceptual framework, design, and implementation of these models, ensuring scalability on the DOE’s leadership computing facilities.

Position Requirements

Required skills, abilities, and knowledge:

• Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied mathematics, or a related field
• Candidates should have expertise in two or more of the following areas:
  • Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
  • Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs)
  • Proficiency in a scientific programming language (e.g., C, C++, Fortran, or Julia)
  • Experience in statistical modeling and probabilistic analysis
• Ability to model Argonne’s core values of impact, safety, respect, impact and teamwork

Preferred skills, abilities, and knowledge:

• Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable
• Experience with parallel computing, large-scale computational science, and simulation of networked physical systems
• Familiarity with techniques for sensitivity analysis and handling high-dimensional problems
• Experience in power grid applications