Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks jobs in United States
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Argonne National Laboratory · 4 months ago

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

Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management. They are seeking a Postdoctoral Appointee to work on uncertainty quantification and modeling of large-scale dynamics in networks, focusing on creating models for electrical power networks and assessing risks associated with rare events.

EnergySecuritySocial Impact
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Culture & Values
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H1B Sponsor Likelynote

Responsibilities

Creating large scale models of dynamic phenomena in electrical power networks
Quantifying the risk of rare events to mitigate vulnerabilities
Responsible for the conceptual framework, design, and implementation of these models
Ensuring scalability on the DOE’s leadership computing facilities

Qualification

Uncertainty quantificationNumerical solutions of differential equationsScientific programming CScientific programming C++Scientific programming FortranScientific programming JuliaStatistical modelingProbabilistic analysisLarge-scale ordinary differential equations (ODEs)Differential-algebraic equations (DAEs)Rare event simulationDeep learningParallel computingLarge-scale computational scienceSimulation of networked physical systemsSensitivity analysisHigh-dimensional problemsPower grid applicationsImpactRespect

Required

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

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

Company

Argonne National Laboratory

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Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management.

H1B Sponsorship

Argonne National Laboratory has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2022 (6)
2021 (2)

Funding

Current Stage
Late Stage
Total Funding
$41.4M
Key Investors
Advanced Research Projects Agency for HealthUS Department of EnergyU.S. Department of Homeland Security
2024-11-14Grant· $21.7M
2023-09-27Grant
2023-01-17Grant

Leadership Team

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Raeanna Sharp- Geiger
COO
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Paul Kearns
Laboratory Director
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Recent News

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