We are always looking for motivated students and researchers to join our team. Whether you’re interested in pursuing a PhD or contributing as an undergraduate/graduate researcher, we welcome applications from individuals passionate about AI-driven manufacturing and energy systems.

We are looking for motivated PhD students interested in AI-driven manufacturing and energy systems. Successful candidates will work on cutting-edge research projects combining physics-based modeling, machine learning, and optimization techniques.

Requirements:

• Strong background in engineering
• Interest in AI and machine learning
• Modeling experience (COMSOL, ANSYS, Simulink, or similar)
• Programming experience (Python, MATLAB, or similar)
• Excellent written and verbal communication skills

What we offer:

• Degree from Rackham Graduate School at University of Michigan
• Competitive stipend and full tuition coverage
• Opportunities to publish in top-tier journals and conferences
• Collaboration with industry partners
• Access to state-of-the-art computational and experimental facilities

How to apply: Please send your CV, transcripts to zhengtl@umich.edu. Include “[PhD Application]” in the beginning of the subject line.

We offer research opportunities for undergraduate and master’s students interested in gaining hands-on experience in AI-driven manufacturing and energy systems research.

Opportunities:

• Potential to get paid research assistant positions
• Independent study and thesis projects
• Opportunities to lead or contribute to publications

How to apply: Please send your Resume/CV and a brief statement of interest to zhengtl@umich.edu. Include “[Researcher Application]” in the beginning of the subject line.

Our research spans multiple areas at the intersection of AI and engineering. We welcome students interested in:

• AI for Manufacturing: Additive manufacturing, battery manufacturing, semiconductor manufacturing
• AI for Energy Storage: Battery thermal management, battery manufacturing, battery recycling
• AI for Data Center HVAC: HVAC system optimization, chip cooling
• AI Methods: Physics-informed machine learning, generative design, uncertainty quantification, surrogate modeling, engineering design optimization

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For questions about joining the lab or to discuss research opportunities, please contact:

• Dr. Zheng Liu
• Assistant Professor
• Industrial and Manufacturing Systems Engineering
• University of Michigan-Dearborn
• 2231 Heinz Prechter Engineering Complex
• 4901 Evergreen Road, Dearborn, MI 48128
• Email: zhengtl@umich.edu

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