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

UNIVERSITY OF TEXAS AT AUSTIN

Austin, TXFellowshipSeen 5 days agoSeen in employer's feed 5 days ago

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At a glance

Compensation
No compensation found
Location
Austin, TX
Role Type
Fellowship
Work Authorization
Not specified

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Job overview

The Postdoctoral Fellow will develop autonomous transmission electron microscopy workflows integrating machine learning, computer vision, automated microscope control, and robotic sample handling. The work includes AI-assisted image interpretation, sample preparation, and linking real-time TEM data to digital-twin and AI platforms. The fellow will collaborate across materials science, data science, and robotics, publish and present research, contribute to proposals, and mentor students and research staff.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningComputer VisionAutomated Microscope ControlDeep LearningPhysics-Informed ModelingRobotic Sample HandlingSample PreparationCloud ComputingDigital TwinsTransmission Electron MicroscopyMentoringResearch Collaboration

Full job description

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-armbased 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 structureproperty 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 Institutes 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.

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