Postdoctoral Associate - Materials Science & Nanoengineering

The NSF-funded READINESS Programmable Cloud Laboratory (PCL) at Rice University invites applications for a Postdoctoral Research Associate to help develop AI-enabled, cloud-accessible autonomous laboratories for next-generation electronic and quantum materials.

The position works at the intersection of materials science, AI for Science, experimental automation, and cloud infrastructure,bridging AI and digital frameworks with physical synthesis andcharacterization systems to enable secure, remotely accessible autonomous experimentation.

We seek a highly motivated researcher at the intersection of materials science, AI for Science, experimental automation, andcloud infrastructure. The successful candidate will bridgeAI/digital frameworks with physical synthesis and characterization systems and help enable secure, remotely accessible autonomous experimentation.

This position is exclusively on-site, necessitating all duties to be performed in-person at Rice University Campus. Per Rice policy
440, work arrangements may be subject to change

$60,000 annually

This is a one year, full-time, benefits eligible position funded bya grant, soft and/or restricted funds, and may be renewed based on continued funding availability, research needs, and performance.

• Ph.D. in Materials Science, or a closely related field.
• No additional experience beyond graduate research required

• Strong experience applying AI/ML to scientific or engineering problems.
• Solid understanding of experimental materials science.
• Strong programming skills, preferably Python.
• Excellent interdisciplinary communication, teamwork, and leadership skills.

• Extensive research experience in AI for Science or a closely related area.
• Experience with autonomous or self-driving laboratories,agentic AI or LLM-based scientific agents, digital twins, Bayesian optimization, or active learning.
• Experience with laboratory automation, instrument control,robotics, materials informatics, cloud computing, scientific data infrastructure, or web-based user-interface development.
• Experience integrating software with laboratory hardware or commercial scientific instruments.

• Develops AI/ML and agentic AI frameworks, digital twins, andclosed-loop optimization workflows for autonomous materials synthesis.
• Connects AI frameworks with physical synthesis andcharacterization instruments through APIs, communication protocols,data pipelines, and hardware/software control interfaces.
• Designs and constructs a web-based user interface andcloud-access framework enabling external users to securely accessand utilize READINESS infrastructure remotely.
• Collaborates with researchers from materials science and computer science, serving as a technical bridge between the two communities.
• Helps lead and mentor a small group of graduate students and publishes research in AI-enabled autonomous experimentation.
• Performs other duties as assigned.

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