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Northwestern Polytechnical University

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PhD Position in Deep Learning at Northwestern Polytechnical University Northwestern Polytechnical University in China

PhD Position in Deep Learning at Northwestern Polytechnical University

Northwestern Polytechnical University

China

Dec 21, 2025

Keywords

Computer Science
Machine Learning
Deep Learning
Artificial Intelligence
Neural Networks

Description

Northwestern Polytechnical University is inviting applications for a PhD position in the area of Deep Learning. The position is supervised by Professor Yongjun Li and is open to motivated and qualified students with a strong background in deep learning methodologies. Applicants should have a CGPA of 3.0 or above, be familiar with deep learning principles and tools, and have prior research experience. Published research papers are considered a strong advantage. The specific research direction will be determined during supervision, but a solid foundation in deep learning is essential. Scholarships are available for qualified candidates in accordance with university and funding regulations. The application deadline is December 21, 2025. Interested candidates are encouraged to reach out with their CV, transcripts, and research interests. Shortlisted applicants will be contacted for the next stage of the selection process. Key research areas include Deep Learning, Machine Learning, Artificial Intelligence, Computer Science, and Neural Networks. This opportunity is ideal for students interested in advancing their expertise in deep learning and contributing to cutting-edge research at Northwestern Polytechnical University in China.

Funding

Scholarships are available for qualified candidates in accordance with university and funding regulations. No specific stipend or funding amount is mentioned.

How to apply

Interested candidates should send their CV, transcripts, and research interests to the supervisor. Shortlisted applicants will be contacted for the next stage.

Requirements

Applicants should have a CGPA of 3.0 or above, strong familiarity with deep learning principles and tools, and prior research experience. Published research papers are considered a strong advantage. A solid foundation in deep learning methodologies is essential.

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