Assistant or Associate Specialist - Department of Civil and Environmental Engineering / P2SL Research Group
The University of California, Berkeley
About this position
Position Overview
Position title: Assistant Specialist Salary range: The UC academic salary scales set the minimum pay determined by rank and step at appointment. See the following tables(s) for the current salary scale(s) for this position: T24 B. The current full-time base salary range for this position is $65,800 -$91,100. Percent time: 100% Anticipated start: Fall 2026 Position duration: One year, with the possibility of reappointment based on performance and availability of funding.
Application Deadline
Open date: August 27, 2026 Next review date:Friday, Sep 11, 2026 at 11:59pm (Pacific Time) Apply by this date to ensure full consideration by the committee. Final date: Monday, Sep 28, 2026 at 11:59pm (Pacific Time) Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Position Description
The Department of Civil and Environmental Engineering (CEE) at UC Berkeley seeks an Assistant or Associate Specialist. The incumbent will develop agentic AI and digital twin technology with Architecture-Engineering-Construction-Facilities Management (AEC-FM) applications in collaboration with Lawrence Livermore National Laboratory (LLNL). Travel to the LLNL site is required as part of the position. Researchers in the Project Production Systems Laboratory (P2SL) use operations science and resilience engineering to deliver capital projects. They also drive process improvements across the AEC-FM domains. The specialist will support the LLNL infrastructure management team in evaluating, designing, and prototyping a building-scale digital twin integrated with agentic AI capabilities. Focusing initially on energy management across LLNL’s STAR buildings, the specialist will document how to expand this technology to a campus-wide scale and other management applications. The specialist will own and execute critical milestones. The duties for this position include: • State-of-the-Practice Review: Conduct a literature review to compile use cases of digital twins using agentic AI in the Architecture, Engineering, Construction, and Facilities Management (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 (e.g., metered power consumption, electricity use, plug loads). • Simulation & Data Modeling: Design a framework, taking into account current and future capabilities at the LLNL, to combine Building Information Modeling (BIM) data, site location features (coordinates, orientation, daylighting), IoT sensor streams, and agentic AI to run and further extend digital twins and associated simulation models. • Reporting & Stakeholder Engagement: Draft deliverables, including comprehensive reports on software/hardware architectures, cybersecurity concerns, and technical summaries for workshops with LLNL and national laboratory personnel.
Qualifications
Basic qualifications(required at time of application)• Bachelor's degree or equivalent international degree. Preferred qualifications• A master’s degree (or equivalent international degree) in Civil Engineering or related field. • Knowledge of Lean Construction, including Choosing by Advantages decision-making system. • Experience or academic exposure to Agentic AI frameworks, machine learning, or autonomous software agents. • Understanding of cybersecurity protocols related to industrial control or infrastructure management systems.
Application Requirements
Document requirementsCurriculum Vitae - Your most recently updated C.V. Cover Letter Reference requirements 3 required (contact information only) Apply link:https://aprecruit.berkeley.edu/JPF05507 Help contact:cwelden@berkeley.edu