Job Description
Position Summary:
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 and characterization 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, and cloud infrastructure. The successful candidate will bridge AI/digital frameworks with physical synthesis and characterization systems and help enable secure, remotely accessible autonomous experimentation.
Special Instructions to Applicants:
Please submit a CV, a brief statement of research interests and relevant experience, and contact information for three references. The statement should highlight experience in AI for Science, experimental materials research, and connecting AI frameworks with physical laboratory and cloud infrastructure.
Workplace Requirements:
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
Hiring Range : $60,000 annually
This is a one year, full-time, benefits eligible position funded by a grant, soft and/or restricted funds, and may be renewed based on continued funding availability, research needs, and performance.
Minimum Requirements:
• Ph.D. in Materials Science, or a closely related field.
• No additional experience beyond graduate research required
Skills:
• 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.
Preferences:
Position Summary:
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 and characterization 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, and cloud infrastructure. The successful candidate will bridge AI/digital frameworks with physical synthesis and characterization systems and help enable secure, remotely accessible autonomous experimentation.
Special Instructions to Applicants:
Please submit a CV, a brief statement of research interests and relevant experience, and contact information for three references. The statement should highlight experience in AI for Science, experimental materials research, and connecting AI frameworks with physical laboratory and cloud infrastructure.
Workplace Requirements:
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
Hiring Range : $60,000 annually
This is a one year, full-time, benefits eligible position funded by a grant, soft and/or restricted funds, and may be renewed based on continued funding availability, research needs, and performance.
Minimum Requirements:
• Ph.D. in Materials Science, or a closely related field.
• No additional experience beyond graduate research required
Skills:
• 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.
Preferences:
- 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.