Computational Research Scientist at Lawrence Berkeley National Laboratory

Berkeley, California, United States -

Full Time

Start Date

Immediate

Expiry Date

01 Jun, 26

Salary

264768.0

Posted On

03 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Independent Research, AI Technologies, Data Curation, Digital Twins, HVAC Systems, Machine Learning Models, Load Forecasting, Agentic AI, Robotics Prototyping, Building Energy Modeling, Simulation Workflow Automation, Technical Reporting, Research Proposal Development, Python Programming, Generative AI, Large Language Models

Industry

Research Services

Description

Lawrence Berkeley National Laboratory is hiring a Computational Research Scientist within the Building and Industrial Energy Systems Division. The Computational Research Scientist will conduct research, develop and apply AI technologies to support design, operation, and retrofit of buildings for optimal performance of energy efficiency, demand flexibility, and occupant comfort. Current research in LBNL’s Building and Industrial Energy Systems Division includes the development and application of building energy simulation, research on building controls, performance monitoring, window systems, high performance facades, management of peak electricity demand, and benchmarking of building energy performance. The incumbent will focus on research and application of advanced AI methods and tools to automate building energy modeling, develop digital twins of buildings, prototype robotic technologies for HVAC systems in buildings, as well as collaborate with BIES staff on related projects. The incumbent will serve as technical lead for projects focusing on AI technologies for buildings. We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes! Why join Berkeley Lab? We invest in our employees by offering a total rewards package you can count on: Exceptional health and retirement benefits, including pension or 401K-style plans Opportunities to grow in your career - check out our Tuition Assistance Program A culture where you’ll belong - we are invested in our teams! In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year. Parental bonding leave (for both mothers and fathers) Pet insurance You will: Conduct independent research, develop and apply advanced AI technologies to curate and integrate data in buildings to be AI-ready Develop and validate digital twins of buildings and HVAC systems Develop and validate machine learning models for load forecasting Conduct independent research and apply AI technologies (e.g., MCP, agentic AI) to automate building energy modeling and simulation workflow Design and prototype robots for HVAC refrigerant leak detection Provide complex troubleshooting and contribute to further development of the LBNL building energy analysis tools: BETTER and CityBES Work effectively both independently and with a team on multi-disciplinary R&D projects Collaborate with project team and PIs on project progress and issues Present projects and research outcomes at conferences and to stakeholders or funders Write technical reports and publish research outcomes as journal articles as lead author Actively contribute to research proposal development, including as lead PI. Successfully build and manage a funded research portfolio. Additional Responsibilities as needed: Manage projects Supervise technical staff We are looking for: An Advanced degree in mechanical engineering, architectural engineering, building science or a closely related field with up to five years’ experience in HVAC or Building Science and Technology, or equivalent work experience. Hands-on experience in developing web-based applications for building energy simulation and analysis Strong experience in curating AI-ready datasets Strong experience in developing digital twins of buildings using EnergyPlus as the simulation engine Strong experience in using machine learning models for load forecasting Strong experience in AI technologies (e.g., MCP, agentic AI) for workflow integration and automation Hands-on experience using data tools (e.g., XML, JSON, YAML, Brick) Strong knowledge of building science and HVAC system operation Strong knowledge of data and computing science Practical knowledge of a wide set of AI technologies Proficiency programming using Python, Python libraries, and AI code packages Strong development skill of web applications Strong skills in using generative AI, large language models Ability to work on multiple tasks and projects Ability to work collaboratively and lead in a team environment Excellent communication skills both oral and written Participate and contribute to research proposal developments Demonstrated ability to publish journal articles Excellent time management skills Desired skills/knowledge: PhD in mechanical engineering, architectural engineering, building science or a closely related field Track records of publication of journal articles General knowledge of project management Requested Application Materials: Curriculum Vitae. Publication list Names and contact information for at least three individuals who can write letters of reference Additional information: Application date: Priority consideration will be given to candidates who apply by March 31, 2026. Applications will be accepted until the job posting is removed. Appointment type:This is a full-time, career appointment, exempt (monthly paid) from overtime pay. Annual salary range: The expected salary for this position is $171,804 - $189,888 which fits into the full salary of $113,028 - $264,768 depending upon the candidate’s skills, knowledge, and abilities. This includes education, certifications, and years of experience. Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment. Work modality: This position is eligible for a hybrid work mode, with 3 to 4 days onsite and 1 to 2 days remote per week. Hybrid work is a combination of teleworking and performing work on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab. Work schedules are dependent on business needs. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here). Relocation: This position is not eligible for relocation assistance. Work authorization: Candidates must be eligible to work in the U.S. at the time of hire. Visa sponsorship is not available for this position. Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law. Berkeley Lab is a University of California employer. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor. Misconduct Disclosure Requirement: 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, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

Responsibilities

The scientist will conduct independent research, develop, and apply advanced AI technologies to prepare building data for AI readiness, focusing on automating energy modeling and developing digital twins of buildings and HVAC systems. Responsibilities also include designing and prototyping robots for HVAC leak detection and contributing to LBNL's building energy analysis tools.