Digital Twin & Agentic-AI Specialist for Building Energy

University of California at Berkeley; Berkeley (CA); On-site; USD 65,000 - 90,000; Full time

Job summary

UC Berkeley's Department of Civil and Environmental Engineering seeks an Assistant or Associate Specialist to develop agentic AI and digital twin technology for AEC-FM applications in collaboration with LLNL. Travel to LLNL is required.

The specialist will build a building-scale prototype integrating real-time energy data and evaluate platforms, drafting technical deliverables for workshops with LLNL and national laboratories.

Qualifications

• Bachelor's degree or equivalent international degree.

Responsibilities

• State-of-the-Practice Review: Conduct a literature review to compile use cases of digital twins using agentic AI in the AECFM sector.
• Platform Evaluation: Identify, compare, and contrast commercial software platforms and off-the-shelf technologies capable of supporting a campus-scale digital twin, assessing compatibility with existing building management systems.
• Methodology & Framework Design: Participate in stakeholder workshops to characterize software platforms and to select optimal application prototypes; assist in applying the Choosing-by-Advantages (CBA) decision-making system during stakeholder workshops.
• Prototype Development: Develop a functional, prototype agentic-AI digital twin at the scale of a building that integrates real-time building energy data.
• Simulation & Data Modeling: Design a framework to combine BIM data, site location features, IoT sensor streams, and agentic AI to run digital twins and simulation models.
• Reporting & Stakeholder Engagement: Draft deliverables, including comprehensive reports on software/hardware architectures and cybersecurity concerns.

Skills

AI concepts

Digital twin

Energy management

Building systems

Research

Education

Bachelor's degree

Tools

BIM software

IoT platforms

CBA decision-making

Job description

UC Berkeley's Department of Civil and Environmental Engineering seeks an Assistant or Associate Specialist to develop agentic AI and digital twin technology for AEC-FM applications in collaboration with LLNL. Travel to LLNL is required.

The specialist will build a building-scale prototype integrating real-time energy data and evaluate platforms, drafting technical deliverables for workshops with LLNL and national laboratories.