The Postdoctoral Position at the University of Arizona's Building Energy and Sustainability Laboratory (BESLab) in the Department of Civil and Architectural Engineering and Mechanics (CAEM) focuses on advancing energy efficiency and decarbonization in smart buildings and cities. Research areas span AI in building control and operations, large language models in human-building interactions, digital infrastructure of buildings, and large-scale urban building energy modeling. The role involves writing proposals and academic papers, lecturing courses, and mentoring PhD students. The candidate must possess a PhD in a relevant architectural engineering, computer science, or relevant field and should have a background in machine learning/deep learning, large language models, building energy modeling, and HVAC systems.

Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more!

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• Lead the writing and submission of at least two research proposals from academia/industry per year.
• Collaborate and assist Dr. Liang Zhang in academic proposal preparation and writing.
• Spearhead the drafting and publication of papers resulting from proposals, preliminary research, and other daily tasks.
• Lend support to Dr. Liang Zhang in producing and drafting academic papers.
• Co-lead the design and daily operation of AI computing lab with Dr. Liang Zhang.
• Deliver up to 5 lectures or lab sessions annually on ARCE 497B Building Energy Modeling.
• Assist Dr. Liang Zhang to supervise and mentor PhD students.

Knowledge, Skills, and Abilities:

• Strong scientific writing skills
• Demonstrated self-motivation, critical thinking, and enthusiasm for scientific research.

• PhD degree in architectural, civil, electrical, mechanical engineering, computer science, or a relevant field.
• Selected candidate must have Ph.D. conferred upon hire.

• Project-based programming experience; independent and collaborative research experience.
• Experience and knowledge in building energy modeling, HVAC systems, machine learning/deep learning, and/or large language models.