À propos de ce poste Postdoctoral Fellow - Transmission Electron Microscopy, Texas Materials Institute, Cockrell School of Engineering chez The University of Texas at Austin
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 the start date of the appointment
Demonstrated experience conducting independent research in a relevant area of materials science or engineering
Strong publication record in peer-reviewed journals
Excellent written and verbal communication skills
Ability to work collaboratively in an interdisciplinary research environment
Commitment to mentoring and contributing to the academic development of graduate and undergraduate students
Preferred Qualifications
- None
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.----
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.----
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.
