Postdoctoral Appointee: AI-Driven Industrial Energy Systems and Supply Chain Modeling
Core
Conduct applied research on AI-driven industrial energy systems optimization, material flow analysis, and supply chain modeling to support U.S. manufacturing resilience and efficiency.
Role type
Postdoctoral Researcher (AI/Operations Research)
Builds
Data-driven analytical tools for industrial capacity planning, logistics optimization, and supply chain analysis.
Domain
Energy Systems & Industrial Supply Chain
Deliverable
production ML models | research | dashboards & analysis
Required skills
AI and machine learning, optimization modeling (linear/mixed-integer/stochastic), statistical analysis, Python/Julia/R, data visualization, reproducible workflow development
Preferred skills
Supply chain network modeling, digital twin methods, Bayesian methods, high-performance computing, geospatial analysis
Technologies
Python, Julia, R, LLMs, scientific computing libraries
Responsibilities
Develop computational models for industrial capacity and logistics; Apply AI/ML to energy systems and supply chains; Integrate data-driven methods with optimization frameworks; Conduct resilience and performance analyses; Build reproducible computational workflows; Develop visualization and decision-support tools; Publish research and present to stakeholders
Seniority
Postdoctoral, hands-on IC
