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Essa Khalil

5 months ago

Fully Funded PhD in Computer Science / AI / Machine Learning at Texas A&M University–Kingsville Texas A&M University–Kingsville in United States

Degree Level

PhD

Field of study

Computer Science

Funding

The PhD position is described as fully funded for Fall 2026.

Deadline

Dec 28, 2026

Country flag

Country

United States

University

Texas A&M University Kingsville

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Keywords

Computer Science
Machine Learning
Electrical Engineering
Information Technology
Artificial Intelligence
Computer Vision
Technical Engineering
Robotics

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About this position

Fully funded PhD opening for Fall 2026 in the PhD in Engineering Program at Texas A&M University–Kingsville.

The project is in Computer Science and focuses on AI / Machine Learning, Computer Vision, and Contrastive Learning. The post says Dr Shaif Chowdhury is seeking one motivated PhD student to join this research area.

Eligibility: applicants should have an MS degree in Computer Science, Engineering, AI/ML, or a related field. The announcement does not mention GRE/IELTS/TOEFL waivers, tuition details, or a specific stipend amount, but it explicitly states the position is fully funded.

How to apply: email your resume/CV to Dr Shaif Chowdhury and use the subject line “PhD Applicant for Fall 2026 - [Applicant Last Name]”. The post does not provide a direct application portal link.

Relevant research keywords: Artificial Intelligence, Machine Learning, Computer Vision, Contrastive Learning, Engineering.

Funding details

The PhD position is described as fully funded for Fall 2026.

What's required

Applicants should have an MS degree in Computer Science, Engineering, AI/ML, or a related area. The post seeks a motivated PhD student interested in AI / Machine Learning, Computer Vision, and Contrastive Learning.

How to apply

Email Dr Shaif Chowdhury with your resume/CV. Use the subject line: 'PhD Applicant for Fall 2026 - [Applicant Last Name]'.

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Professors

Professor at Texas A&M University–Kingsville

University Name
Country flag

United States

Research Interests

Artificial Intelligence

Technical Engineering

Computer Science

Machine Learning

Computer Vision