Postdoctoral Fellow - Multiple Teams

Job Posting Title:

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

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Hiring Department:

Walker Department of Mechanical Engineering

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Position Open To:

All Applicants

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Weekly Scheduled Hours:

40

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FLSA Status:

Exempt

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Earliest Start Date:

Immediately

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Position Duration:

Expected to Continue Until Aug 31, 2027

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Location:

UT MAIN CAMPUS

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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 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.

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 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 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 materials research laboratories at UT Austin

• Performs other related duties as assigned

Required Qualifications

• Ph.D. in Materials Science, Computer Science, Engineering, Applied Physics, or a closely related field, conferred within three (3) years before the start date of the appointment

• Strong proficiency in Python and modern ML and agentic AI frameworks

• Experience with control, optimization, or reinforcement learning, OR workflow automation / multi-agent systems

• Demonstrated experience conducting independent research in a relevant area of materials science or engineering

• Strong publication record in peer-reviewed journals/conferences

• Excellent written and verbal communication skills

• Ability to work collaboratively in an interdisciplinary research environment. Comfort working with real-world experimental environments, including handling uncertainty, noise, and incomplete data

• Commitment to mentoring and contributing to the academic development of graduate and undergraduate students

Salary

$61,093

Working Conditions

• May work around standard office conditions

• Repetitive use of a keyboard at a workstation

• Use of manual dexterity

Required Materials

• Resume/CV

• Letter of interest

• 3 work references with their contact information; at least one reference should be from a supervisor

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume in the first step of the online job application process. Then, any additional Required Materials will be uploaded in the My Experience section; you can multi-select the additional files or click the Upload button for each file. Before submitting your online job application, ensure that ALL Required Materials have been uploaded.  Once your job application has been submitted, you cannot make changes.

Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find Jobs. Before you apply, though, log in to Workday, navigate to your Worker Profile, click the Career link in the left-hand navigation menu, and then update the sections in your Professional Profile. This information will be pulled into your application. The application is one page, and you will need to click the Upload button multiple times in order to attach your Resume, References, and any additional Required Materials noted above.

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Employment Eligibility:

Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation.

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Retirement Plan Eligibility:

The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.

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Background Checks:

A criminal history background check will be required for finalist(s) under consideration for this position.

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Equal Opportunity Employer:

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

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Pay Transparency:

The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.

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Employment Eligibility Verification:

If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.  You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States.  Documents need to be presented no later than the third day of employment.  Failure to do so will result in loss of employment at the university.

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E-Verify:

The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:

• E-Verify Poster (English and Spanish) [PDF]
• Right to Work Poster (English) [PDF]
• Right to Work Poster (Spanish) [PDF]

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Compliance:

Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.

The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.