Postdoctoral Appointee: Physics-Informed AI for Microelectronics Materials jobs in United States
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Argonne National Laboratory · 3 weeks ago

Postdoctoral Appointee: Physics-Informed AI for Microelectronics Materials

Argonne National Laboratory is seeking a postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials. The role involves developing frameworks that integrate heterogeneous data from simulations and experiments to understand complex material phenomena across scales.

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Responsibilities

Design, implement, and validate physics-informed AI/ML models for microelectronics materials
Curate, manage, and integrate heterogeneous datasets from experiments and simulations
Collaborate closely with experimental teams to benchmark and refine computational models
Disseminate research through publications, presentations, and open-source contribution

Qualification

PythonMachine Learning frameworksManaging multimodal datasetsAI/ML conceptsHigh-performance computingPhysics-based simulationsTraining AI/ML modelsCollaboration with experimental teamsInterest in interfacial phenomenaTeamwork

Required

Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field
Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) applied to scientific problems
Strong background in managing multimodal datasets
Proven experience collaborating with experimental teams to validate computational models
Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork

Preferred

Deep understanding of AI/ML concepts, including transformers, latent-space representations, generative models, and reinforcement learning
Experience with high-performance computing, physics-based simulations, and multimodal data workflows
Demonstrated ability to train and deploy AI/ML models using simulated and experimental data
Familiarity with agentic LLM-based approaches and related technologies (e.g., RAG, MCP, A2A)
Interest in interfacial phenomena and defect dynamics in materials across scales

Benefits

Comprehensive benefits are part of the total rewards package

Company

Argonne National Laboratory

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

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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