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Postdoc Positions: If you are interested in joining us, please contact Sanfeng (sanfengw at princeton dot edu). Opportunities for postdoctoral fellowships: Dicke Fellowship; PCCM Postdoctoral Fellowship; PQI Fellowship. 

Highlighted Openning (2026):

Postdoctoral Researcher – AI for Quantum Materials

Department of Physics & Department of Electrical and Computer Engineering, Princeton

Princeton AI Lab / Princeton Quantum Initiative

Position Description

We are seeking a highly motivated and talented Postdoctoral Research Associate to join a pioneering, cross-disciplinary research initiative at Princeton University. This position is jointly supervised by Professor Sanfeng Wu (Experimental Condensed Matter Physics/Princeton Quantum Initiative) and Professor Mengdi Wang (Electrical and Computer Engineering/Princeton AI Lab).

The successful candidate will spearhead the new frontier of AI for Quantum Materials, specifically focusing on integrating advanced machine learning, large language models (LLMs), robotics, world models, and autonomous agentic systems into the experimental workflow and discovery of quantum materials. The project aims to advance and refine autonomous experimental platforms capable of closed-loop reasoning, planning, and real-time physical execution, ranging from novel material synthesis to the automated fabrication and characterization of complex nanodevices.

This role offers a unique ecosystem: embedding the candidate directly within the state-of-the-art quantum materials laboratory while maintaining a deep, collaborative footing inside Princeton’s leading artificial intelligence community.

Key Responsibilities

• Core Research: Enable new scientific frontiers of quantum materials discoveries using AI; Develop, deploy, and optimize AI algorithms, models and agentic frameworks tailored for physical laboratory automation, hardware control, and real-time experimental decision-making; Discover new quantum materials or physical phenomena.

• Cross-Disciplinary Collaboration: Work at the intersection of AI, scientific instrumentation, robotics, quantum materials synthesis and characterization;  Collaborate closely with experimental physicists, material scientists, and computer science theorists; Design intelligent pipelines for the AI-accelerated characterization, synthesis, and discovery of novel quantum materials and devices.

Required Qualifications

• A Ph.D. in Physics, Computer Science, Electrical Engineering, Materials Science, or a closely related field.

• A strong track record of publication and research excellence.

• Deep curiosity for both AI and quantum materials science, with demonstrated experience in at least one of the primary domains (multimodal AI/agentic systems/world models or experimental condensed matter physics/quantum materials/solid state chemistry).

• Excellent communication skills and ability to collaborate productively across traditional disciplinary boundaries.

Preferred Technical Skills (Varying by Candidate Background)

• For candidates with AI/CS background: Experience with LLM/VLM, AI agents, reinforcement learning, world models, computer vision, or robotics/hardware control interfaces.

• For candidates with Quantum Materials background: Experience with quantum material synthesis, 2D materials and nanofabrication, electronic transport measurement, low temperature electronics.

How to Apply

Interested candidates should submit a CV, a 2-page research statement including summary of past achievements and future plan, and contact information for three references to Prof Sanfeng Wu (sanfengw@princeton.edu). Letters of reference will only be requested for shortlisted candidates.

Graduate and Undergraduate Students: We always look for graduate and undergraduate students with strong self-motivation to join us. If you are interested in experimental condensed matter physics, physical AI, nanodevices, or future quantum technologies, don't hesitate to explore in depth this website and/or visit us in the lab. For application, please email Sanfeng (sanfengw at princeton dot edu).

Candidates with a background and an interest in any of the following fields will be considered: LLM, world models, 2D materials, mK electronics, optics, crystal synthesis and robotics.