Jun Zhang, PhD, is a Distinguished Associate Researcher and Assistant Professor at Shenzhen University.
Email: junzhang@szu.edu.cn
He received his PhD in Computer Science and Technology from Harbin Institute of Technology in 2022 and joined the National Engineering Laboratory for Big Data System Computing Technology at Shenzhen University in 2023. He is a Class C Talent of Shenzhen Pengcheng Peacock Program and a member of the Bioinformatics Committee and Natural Language Processing Committee of the China Computer Federation (CCF). His main research areas include bioinformatics, machine learning, natural language processing, and computer-aided drug design. He is dedicated to solving challenging problems in bioinformatics, such as the identification and optimization of protein-nucleic acid interactions and the synthesis of nucleic acid aptamers, using theories and technologies from machine learning and natural language processing. In the past five years, he has published over 20 academic papers in important journals such as Trends in Genetics, Bioinformatics, Briefings in Bioinformatics, and IEEE-ACM Transactions on Computational Biology and Bioinformatics, with one paper selected as an ESI highly cited paper. He has also co-authored one book. He has led projects funded by the National Natural Science Foundation of China (NSFC) for Young Scientists, the Guangdong Provincial Natural Science Foundation, the Shenzhen High-Level Talents Startup Project, and a key internal project of the National Engineering Laboratory for Big Data. He has received numerous honors, including the National Graduate Scholarship and the title of Outstanding Master's Graduate from Harbin Institute of Technology. He serves as a reviewer for several international journals and conferences, including *Briefings in Bioinformatics*, *Trends in Analytical Chemistry*, and *Communication Biology*.
Current Research Topics:
- Bioinformatics: Large-scale models of biological language, identification and optimization of protein-nucleic acid interactions, protein and peptide design
- Machine Learning: Unsupervised representation learning, reinforcement learning, graph neural networks
Openings: Postdoctoral fellows and research assistants are being recruited; two master's students (2025 cohort) and one joint-training doctoral student are also welcome. Students and master's/doctoral graduates interested in the above areas are welcome to contact me!
Specific Requirements: Diligent and hardworking, with a good foundation in programming, mathematics, and English, and relatively independent thinking ability.
Some research results:
1. Junhang Cao#, Jun Zhang#, Qiyuan Yu, Junkai Ji, Jianqiang Li, Shan He, Zexuan Zhu. TG-CDDPM: text-guided antimicrobial peptides generation based on conditional denoising diffusion probabilistic model[J]. Briefings in Bioinformatics. 2025, 26(1):bbae644. (District 1, Chinese Academy of Sciences, CCF Class B)
2. Jun Zhang, Mei Lang, Yaoqi Zhou, Yang Zhang. Predicting RNA structures and functions by artificial intelligence[J]. Trends in Genetics. 2024., 40(1): 94-107. (District 1, Chinese Academy of Sciences)
3. Jun Zhang, Ke Yan, Qingcai Chen, Bin Liu. PreRBP-TL: prediction of species-specific RNA-binding proteins based on transfer learning[J]. Bioinformatics. 2022, 38(8): 2135–2143. (CCF Category B)
4. Jun Zhang, Qingcai Chen, Bin Liu. NCBRPred: predicting nucleic acid binding residues in proteins based on multilabel learning[J]. Briefings in Bioinformatics. 2021, 22(5): bbaa397. (CAS Zone 1, CCF Category B)
5. Jun Zhang, Qingcai Chen, Bin Liu. iDRBP_MMC: Identifying DNA-Binding Proteins and RNA-Binding Proteins Based on Multi-Label Learning Model and Motif-Based Convolutional Neural Network[J]. Journal of Molecular Biology. 2020, 432(22): 5860-5875. (CAS Zone 2)
Personal Homepage: https://www.researchgate.net/profile/Jun-Zhang-222
