Yi Sheng
5 months ago
PhD Position in Efficient Deep Learning, Edge AI, and Medical AI Systems at University of South Florida University of South Florida in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
December 31, 2026Country
United States
University
University of South Florida

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About this position
The YES Lab (Yi Sheng's Lab for Efficient and Scalable AI Systems) at the University of South Florida is seeking a talented PhD student to join their research team. The lab focuses on cutting-edge research in efficient deep learning, edge AI, AI/ML for medical systems, and hardware-aware model optimization. Students will have the opportunity to work closely with Professor Yi Sheng, an experienced mentor, and collaborate with top researchers from other institutions.
Key research areas include developing scalable and efficient artificial intelligence systems, optimizing machine learning models for hardware constraints, and applying AI/ML techniques to medical systems. The position is ideal for candidates passionate about making AI more efficient and impactful in real-world applications.
Applicants should have a strong background in computer science, artificial intelligence, or related fields. Required application materials include transcripts, CV, and language proficiency documentation. While the post does not specify funding details, it is implied to be a funded PhD position. Interested candidates are encouraged to contact Professor Yi Sheng via email or LinkedIn for more information and to apply.
For more details, visit the YES Lab or connect with Professor Yi Sheng on LinkedIn.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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