Publisher
source

Johns Hopkins University

Top university

PhD position The Johns Hopkins University in United States

Degree Level

PhD

Field of study

Computer Science

Funding

The position is fully funded, covering tuition and providing a stipend. No further financial details are specified.

Deadline

Dec 28, 2026

Country flag

Country

United States

University

Johns Hopkins University

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Keywords

Computer Science
Data Science
Machine Learning
Artificial Intelligence
Health Science
Computer Vision
Healthcare Delivery
Biomedical Applications

About this position

The LDR Group at Johns Hopkins University, led by Peirong Liu, is recruiting a fully-funded PhD student to start in Fall 2026. The group conducts interdisciplinary research in artificial intelligence, with a particular emphasis on machine learning, computer vision, and healthcare/biomedical applications. Projects often involve working with diverse and imperfect real-world data, including images, videos, text, voice, and signals, across multiple scales from molecules to populations.

The group aims to develop foundational theories and practical algorithms for healthcare, translating scientific discoveries into real-world impact. Applicants should have a strong mathematical background and coding skills in machine learning and computer vision.

Prior research experience in healthcare or biomedical fields is advantageous but not mandatory. The position is fully funded, including tuition and stipend. Interested candidates should email Peirong Liu with their CV, transcripts, and a brief summary of their background and research interests, using the subject 'Prospective PhD 2026'.

Funding details

The position is fully funded, covering tuition and providing a stipend. No further financial details are specified.

What's required

Applicants should be self-motivated students with a solid mathematical background and strong coding skills in machine learning and computer vision. Research experience in healthcare and biomedical applications is a plus but not required. Candidates should be able to provide a CV, transcripts, and a brief summary of their background and research interests.

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