Postdoctoral Fellow - Transmission Electron Microscopy, Texas Materials Institute, Cockrell Sch

Postdoctoral Fellow - Transmission Electron Microscopy, Texas Materials Institute, Cockrell School of Engineering

flexible benefit account, sick time, tuition assistance, 403(b), retirement plan, employee discount

Hiring Department: Texas Materials Institute

Position Open To: All Applicants

Weekly Scheduled

Hours:

40

FLSA Status: Exempt

Earliest

Start Date:

Immediately

Position Duration: Expected to Continue Until Aug 31, 2027

Location: UT MAIN CAMPUS

Job Details:

As a top‑10 engineering school with the No. 1 program in Texas, the Cockrell School of Engineering at The University of Texas at Austin has been a global leader in technology innovation and engineering education for over a century. With 11 undergraduate and 13 graduate programs, over 20 research centers and a faculty community that boasts one of the highest numbers of National Academy of Engineering members among U.S. universities, Texas Engineering has launched some of the nation’s most accomplished leaders and pioneered world‑changing solutions in virtually every industry, from space exploration to energy to health care.

Situated in the heart of Austin — named “America’s Coolest City” by Expedia and “The Best Place to Live in the U.S.” by U.S. News and World Report — the Cockrell School embodies the city’s innovative spirit. Major companies with Austin campuses, such as Dell, National Instruments, Apple, IBM, Samsung, Google, and many others, continue to recruit Cockrell School students at a remarkable rate, launching thousands of successful careers and developing Texas Engineers into industry leaders.

The Postdoctoral Fellow will lead research in AI‑driven and self‑driving transmission electron microscopy (TEM) as part of the advanced materials characterization and autonomous discovery initiatives within the Texas Materials Institute (TMI) at The University of Texas s position focuses on developing the next generation of intelligent electron microscopy systems that integrate machine learning, robotic control, and real‑time data analysis to achieve autonomous imaging and interpretation of complex materials systems.

The Fellow will design and execute experiments that advance the frontier of self‑optimizing microscopy, including automated alignment, adaptive focusing, drift correction, and AI‑assisted atomic structure recognition. The role involves building and training deep‑learning models for TEM image reconstruction and interpretation, linking image features to local chemistry, defects, and dynamic transformations under varying environmental or beam conditions. The successful candidate will work closely with faculty and research staff to help establish TMI’s new AI‑integrated microscopy hub as a national leader in self‑driving electron microscopy.

• Develop and implement self‑driving TEM workflows that integrate machine learning, computer vision, and automated microscope control for autonomous imaging, focusing, and data acquisition.

• Advance AI‑assisted image interpretation, including atomic structure recognition, defect classification, and dynamic process tracking using deep‑learning and physics‑informed models.

• Integrate TEM operations with robotic sample handling, including the design, testing, and deployment of a robot‑arm‑based TEM grid‑loading and exchange system for continuous, unattended operation.

• Collaborate with postdoctoral fellows in liquid‑phase synthesis and microdroplet printing to establish seamless sample transfer pipelines from synthesis to TEM analysis, enabling high‑throughput, correlative characterization.

• Develop and optimize sample preparation methods compatible with microdroplet‑printed thin films, nanoparticle arrays, and electrochemical catalyst systems, ensuring reproducible and contamination‑free data.

• Link real‑time TEM data streams to digital twin and AI platforms, using cloud‑based computation for adaptive experiment control, hypothesis generation, and structure‑property modelling.

• Publish high‑impact research, present findings at international conferences, and contribute to proposal development for new AI‑in‑microscopy and autonomous discovery initiatives.

• Mentor graduate students and research…