Texas A&M University
4 days ago
Fully Funded PhD/GRA Opportunities in Transportation, Logistics, and AI for Resilient Systems Texas A&M University in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded Graduate Research Assistantship opportunities are possibly available. Funding includes tuition support and a competitive stipend.
Country
United States
University
Texas A&M University

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About this position
Fully funded Graduate Research Assistantship (GRA) opportunities are possibly available in the Advanced Transportation, Logistics & AI for Resilient Systems (ATLAS) Lab at Texas A&M University, USA.
The lab focuses on research areas connected to transportation, logistics, artificial intelligence, resilient systems, operations research, computer science, data science, machine learning, statistics, and mathematics. Prospective students are encouraged to review the lab’s prior publications and research profiles to understand the methodologies and application areas represented in the group.
Funding, if selected, includes tuition support and a competitive stipend.
This opportunity is for students interested in joining in Spring 2027 or a later term. Applicants should send a CV, unofficial transcripts, and a brief 1–2 paragraph statement explaining their research interests and identifying the ATLAS thrust or topics that best align with their background.
Contact emails mentioned in the post are [email protected] and [email protected].
Funding details
Fully funded Graduate Research Assistantship opportunities are possibly available. Funding includes tuition support and a competitive stipend.
What's required
Interested applicants should be joining in Spring 2027 or later. Applicants should email a CV, unofficial transcripts, and a brief 1-2 paragraph statement describing research interests and the ATLAS thrust/topics that best match their background. The post asks applicants to review prior publications and research profiles to understand the lab's methodologies and application areas.
How to apply
Email your CV, unofficial transcripts, and a brief statement of research interests to [email protected] and [email protected]. Review the lab's prior publications and research profiles before contacting them.
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