Assistant or Associate Specialist - Department of Civil and Environmental Engineering / P2SL Research Group University of California Berkeley - 4.2 Berkeley, CA Job Details Full-time $65,800 - $91,100 a year 18 hours ago Qualifications Bachelor's degree Stakeholder management Full Job Description 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 Window 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 requirements Curriculum 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: About UC Berkeley UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy ( APM 210 1-d ). These values are embedded in our Principles of Community , which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive. The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy . In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter. As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements. Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee. As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct. "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer. UC Sexual Violence and Sexual Harassment Policy UC Anti-Discrimination Policy

APM - 035

Affirmative Action and Nondiscrimination in Employment Job location Berkeley, CA To apply, visit https://aprecruit.berkeley.edu/JPF05507 je-447ded2c46e040d7ae4e9957290280fd