AI-Driven TEM Fellow: Autonomous Imaging

University of Texas; Utah; On-site; USD 55,000 - 67,000; Full time

Benefits offered by this job

Competitive health benefits

Paid time off and holidays

Tuition assistance

Job summary

The University of Texas at Austin's Texas Materials Institute invites applications for a Postdoctoral Fellow in Transmission Electron Microscopy. The role leads AI-driven TEM research, integrating machine learning, robotic control, and real-time data analysis for autonomous imaging and interpretation of materials.

The fellow will design experiments, train deep-learning models for TEM reconstruction, mentor students, and help build AI-enabled microscopy facilities within the autonomous discovery

Qualifications

• Ph.D. in Materials Science, Engineering, Physics, Chemistry, or related field.
• Demonstrated independent research in a relevant area.
• Strong publication record in peer-reviewed journals.
• Excellent written and verbal communication skills.
• Ability to collaborate across disciplines.
• Commitment to mentoring graduate and undergraduate students.

Responsibilities

• Develop self-driving TEM workflows integrating ML, vision, and automated control.
• Advance AI-assisted image interpretation and defect classification.
• Collaborate on robotic TEM grid handling and sample transfer systems.
• Publish high-impact research and contribute to funding proposals.
• Mentor graduate students and junior researchers.

Skills

Independent research

Publications

Written communication

Verbal communication

Collaborative work

Mentoring

Education

Ph.D. in Materials Science, Engineering, Physics, or Chemistry

Job description

The University of Texas at Austin's Texas Materials Institute invites applications for a Postdoctoral Fellow in Transmission Electron Microscopy. The role leads AI-driven TEM research, integrating machine learning, robotic control, and real-time data analysis for autonomous imaging and interpretation of materials.

The fellow will design experiments, train deep-learning models for TEM reconstruction, mentor students, and help build AI-enabled microscopy facilities within the autonomous discovery