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Flex Material Science Postdoc Jobs in Texas (NOW HIRING)

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Flex Material Science Postdoc information

What is the difference between Flex Material Science Postdoc vs Flex Material Engineer?

AspectFlex Material Science PostdocFlex Material Engineer
Required CredentialsPhD in Materials Science, Chemistry, or related fieldBachelor's or Master's in Materials Engineering, Mechanical Engineering, or related field; sometimes a PhD
Work EnvironmentResearch laboratories, academic settings, corporate R&DProduct development labs, manufacturing facilities, corporate offices
Employer & Industry UsageUniversities, research institutes, corporate R&D teamsElectronics, flexible device manufacturing, consumer electronics companies

The Flex Material Science Postdoc typically focuses on research, experimentation, and advancing new materials, often in academic or corporate R&D settings. In contrast, the Flex Material Engineer applies existing material knowledge to develop, test, and implement flexible materials in products. While both roles require a strong background in materials science, the Postdoc emphasizes research, whereas the Engineer emphasizes practical application and product development.

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The most popular types of Material Science Postdoc jobs in Texas are:

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For Flex Material Science Postdoc jobs in Texas, the most frequently searched job titles are:

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What cities in Texas are hiring for Flex Material Science Postdoc jobs?

Cities in Texas with the most Flex Material Science Postdoc job openings:

Flex Material Science Postdoc jobs near you
Infographic showing various Flex Material Science Postdoc job openings in Texas as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 72% Full Time, 23% Part Time, and 3% Contract. Highlights an 76% Physical, 3% Hybrid, and 21% Remote job distribution.

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

The University of Texas at Austin

Austin, TX • On-site

$48K - $65K/yr

Full-time

Re-posted 28 days ago

University Of Texas at Austin rating

8.3

Company rating: 8.3 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

129th of 622 rated colleges and universities

Job description

Job Summary:
The University of Texas at Austin is a top-10 engineering school and is seeking a Postdoctoral Fellow to lead research in agentic AI and autonomous laboratory systems. The role focuses on developing AI agents and frameworks for intelligent experimental workflows to automate complex decision-making in materials discovery.
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
Qualifications:
Required:
• 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
Company:
The University of Texas at Austin is one of the largest public universities in the United States. Founded in 1883, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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