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

Job Posting Title:

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

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:

General Notes

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 number 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.

At UT Austin, we say “What starts here changes the world.” As a member of the university community, you will be part of an organization that is internationally recognized for our academic programs and research. Your work will have meaning and make a difference not only in the lives of our faculty, staff, and students, but also those who are impacted by our first-class academic and research programs.

UT Austin provides outstanding employee benefits and total rewards packages that include:

Competitive health benefits (employee premiums covered at 100%, family premiums at 50%)

Voluntary Vision, Dental, Life, and Disability insurance options

Generous paid vacation, sick time, and holidays

Teachers Retirement System of Texas, a defined benefit retirement plan, with 7.75% employer matching funds

Additional Voluntary Retirement Programs: Tax Sheltered Annuity 403(b) and a Deferred Compensation program 457(b)

Flexible spending account options for medical and childcare expenses

Robust free training access through LinkedIn Learning, plus professional conference opportunities

Tuition assistance

Expansive employee discount program, including athletic tickets

Free access to UT Austin's libraries and museums with staff ID card

Free rides on all UT Shuttle and Austin CapMetro buses with staff ID card

Purpose

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 at Austin. This 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.

This position will operate as a core part of a larger AI-robotic materials discovery program at TMI that couples liquid-phase synthesis, high-throughput sample processing, and autonomous characterization. The TEM postdoctoral fellow will collaborate with companion postdocs specializing in liquid-phase synthesis and thin-film formation, integrating structural characterization directly with compositional and processing data streams. A central aspect of this work will be to interface TEM workflows with the microdroplet printing system for high-throughput sample deposition onto TEM grids or micro-electrode arrays, enabling statistically rich structure–property correlations across thousands of printed materials. The Fellow will also contribute to the development of robotic sample preparation and automated sample-loading systems, including a robot arm-based TEM grid handling and holder-loading setup, to achieve continuous, unsupervised operation of the microscope. Working within this integrated ecosystem, the Fellow will help connect real-time TEM data to cloud-based digital twins and the broader AI framework controlling synthesis and electrochemical testing, creating a closed experimental–computational feedback loop for autonomous materials discovery.

The Postdoctoral Fellow will be expected to lead and publish independent research, collaborate across disciplines of materials science, electron microscopy, chemistry, and data science, and contribute to the mentorship of graduate students and junior researchers. Additional responsibilities include developing new experimental protocols, contributing to multi-PI proposals, and helping define the architecture for fully autonomous electron microscopy systems. This position offers a unique opportunity to be at the forefront of AI-driven discovery science, operating at the interface between robotic automation, advanced electron microscopy, and intelligent materials design.

Responsibilities

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 modeling.

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 staff, fostering interdisciplinary collaboration between materials science, data science, and robotics.

Collaborate with the Texas Materials Institute’s instrumentation and AI engineering teams to help define the architecture for next-generation autonomous TEM facilities at UT Austin.

Performs other related duties as assigned.

Required Qualifications

Ph.D. in Materials Science, Engineering, Physics, Chemistry, or a closely related field, conferred within three (3) years before th