Postdoctoral Fellow - TMI, Agentic AI, Texas Materials Institute, Cockrell School of Engineering

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 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.

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.

Purpose

The Postdoctoral Fellow will lead research in agentic AI and autonomous laboratory systems as part of the advanced materials characterization and discovery initiatives within the Texas Materials Institute (TMI) at The University of Texas at Austin. This position is centered on developing AI agents and agentic orchestration frameworks capable of observing, reasoning, planning, and acting across multiple classes of scientific instruments, enabling a fully integrated closed-loop “self-driving laboratory”. The role focuses on providing the AI core and foundational intelligence that coordinates the entire experimental ecosystem.

The Postdoctoral Fellow will develop agentic AI models and frameworks for intelligent experimental workflows, which couple machine learning, real-time data analysis, and tool-use APIs to automate complex decision-making across materials design, liquid-phase synthesis, and characterization platforms. Responsibilities include building agentic AI systems that can interpret multimodal data streams, interface with instrument control systems, and autonomously execute experimental tasks with minimal human intervention.

The Postdoctoral Fellow will be responsible for both developing and deploying agentic AI systems in real laboratory environments, ensuring robust performance under real-world noise, uncertainty, and instrument variability. This position is embedded within TMI’s larger AI-robotic materials discovery program, which integrates liquid-phase synthesis, high-throughput sample processing, and autonomous characterization. The Postdoctoral Fellow will collaborate closely with companion researchers in synthesis and characterization and will provide the foundational AI layer that enables these autonomous workflows. The agentic AI systems developed through this position are expected to interface seamlessly with high-throughput deposition tools, robotic sample-handling infrastructure, and adaptive characterization routines. Working within this highly integrated environment, the Postdoctoral Fellow will contribute to establishing a continuous experimental–computational feedback loop, in which real-time measurements feed directly into AI reasoning layers and digital twins, and autonomous agents determine the next experiments needed for accelerated materials discovery.

The emphasis of this position is the creation of system-level intelligent automation, where multiple scientific instruments are coordinated through a unified agentic AI framework. The Postdoctoral Fellow will be expected to lead and publish independent research, collaborate across disciplines of computer science, materials science, electron microscopy, chemistry, and data science, and contribute to the mentorship of graduate students and junior researchers. Additional responsibilities include developing new protocols for experimental AI agents, 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 agentic AI models and agentic orchestration frameworks for multi-step, multi-instrument experimental workflows (e.g., observe–reason–plan–act). Design closed-loop optimization and active learning strategies for real-time experiment steering and adaptive decision-making
• Integrate agentic AI systems with instrument control APIs, laboratory scheduling systems, and data acquisition interfaces, enabling autonomous operation across diverse scientific instruments
• Build and refine digital twins for synthesis and characterization workflows, using physics-based simulations and/or surrogate ML models
• Collaborate closely with experimentalists, theorists, and engineers across academic and industrial partners. Work with postdoctoral fellows in liquid-phase synthesis, microdroplet printing, and characterization
• Publish high-impact research, present findings at international conferences, and contribute to proposal development for new initiatives in agentic AI and autonomous laboratory systems
• Mentor graduate students and research staff, fostering interdisciplinary collaboration