The project is hiring 1 research assistant at SUSTech
南方科技大学课题组现公开招聘科研助理1名。
Title/项目名称
Mathematical Methods in Computational Microscopy
计算显微成像中的数学方法
Abstract/项目简介
This joint research project aims to develop novel mathematical models and computational algorithms to address critical challenges in computational microscopy. By integrating advanced mathematical tools, such as sparse representation, low-rank tensor recovery, optimization, and physics-informed deep learning, with cutting-edge microscopy techniques (e.g., optical, X-ray, and electron microscopy), the project seeks to push the physical limits of traditional imaging. The developed methodologies will be applied to transdisciplinary fields, with a particular focus on the high-fidelity reconstruction and multi-dimensional characterization of battery materials and biological samples, ultimately accelerating scientific discovery and industrial applications.
本项目旨在开发新型数学模型与计算算法，以解决计算显微成像中的关键挑战。通过将先进的数学工具（如稀疏表示、低秩张量恢复、最优化方法以及物理驱动的深度学习）与前沿的显微成像技术（如光学、X射线和电子显微镜）深度交叉融合，本项目致力于突破传统成像的物理极限。所开发的方法学将广泛应用于跨学科领域，特别是针对电池材料与生物样本的高保真三维重建与多维表征，最终加速相关领域的科学发现与工业应用进程。
Reference:
[1] T. Wang, et al. “Data-driven deformation correction in X-ray spectro-tomography with implicit neural networks.” Patterns (2026),
101515, https://doi.org/10.1016/j.patter.2026.101515
[2] C. Huang, et al. "Dopamine-mediated interactions between short-and long-term memory dynamics." Nature 634.8036 (2024): 1141-1149.
[3] S. Haziza, et al. "Imaging high-frequency voltage dynamics in multiple neuron classes of behaving mammals." Cell 188.16 (2025): 4401-4423.
[4] T. Wang, et al. "Hyperspectral and Multispectral Image Fusion with Arbitrary Resolution Through Self-Supervised Representations." International Journal of Computer Vision 133.11 (2025): 7515-7535.
PI at SUSTech
Dr. Chao Wang （王超博士）
Dr. Wang is an Assistant Professor of the Department of Statistics and Data Science at Southern University of Science and Technology. His research directions are mainly image processing, scientific computing, and interdisciplinary data science, and he has made some innovative contributions to theoretical and algorithmic aspects of sparsity. In recent years, he has published or accepted more than 30 papers as the first or corresponding author in prestigious journals and conferences. These include 1 paper in Cell subjournal, 5 papers in the SIAM series, 3 in the IEEE Q1 series, and 6 in CCF A-level journals/conferences. The applicant was selected for the Guangdong Young Pearl River Scholar, and his work has received multiple awards, including the Best Paper Award at a CVPR workshop, the Student Paper Award at the CSIAM Annual Meeting, and 2 SIAM travel awards.
Research Group Website: https://wangcmath.github.io/
王超，是南方科技大学统计与数据科学系的助理教授（副研究员）。他的研究方向主要是图像处理、科学计算和跨学科数据科学，并在稀疏性方面研究取得了一些创新性的理论和算法进展。近年来，以第一作者或通讯作者身份在领域内权威期刊及会议发表（含录用）论文30余篇，包括1篇Cell子刊、5篇SIAM系列、3篇一区IEEE系列以及6篇CCF-A类文章等。申请人入选广东青年珠江学者，获CVPR研讨会最佳论文奖，CSIAM年会学生论文奖，以及2次获得SIAM差旅奖。
课题组网页：https://wangcmath.github.io/
PI at CUHK
Dr. Jizhou Li (李济舟博士)
Dr. Jizhou Li is currently a Vice-Chancellor Assistant Professor at the Department of Electronic Engineering, The Chinese University of Hong Kong. With his interdisciplinary background in mathematics and engineering, Dr. Li has consistently pursued advancements in the field of transdisciplinary imaging science, advancing both the methodologies and applications of various microscopy techniques, including optical, X-ray, and electron microscopy. His recent research focuses on developing computational microscopy techniques for battery material characterization, promoting the application of signal processing and computational imaging in materials science research and industrialization processes, thereby accelerating the design and development of high-performance battery materials. In recent years, he has published over 60 peer-reviewed articles in prestigious journals and conferences, including Science, Nature, Cell, and their sister journals, PNAS, Advanced Materials, and IEEE Transactions. He has received multiple awards from IEEE and SIAM, including two Best Conference Paper Awards from the IEEE Signal Processing Society and the Engineering in Medicine and Biology Society, as well as a CVPR Best Paper Award Finalist from the IEEE Computer Society. He is a Senior Member of IEEE.
Research Group Website: https://www.aimicroscopy.org/
李济舟, 现任香港中文大学电子工程系校长特聘助理教授(Vice-Chancellor Assistant Professor)。凭借数学和工程学的交叉背景，李教授一直致力于推动跨学科成像科学领域的进步，促进了包括光学、X射线和电子显微镜在内的多种显微成像技术在方法学和应用上的发展。其近期的研究重点在于发展用于电池材料表征的计算显微成像技术， 推动信号处理与计算成像在材料科学研究及工业化过程中的应用，从而加速高性能电池材料的设计与发展。他近年来在Science/Nature/Cell及其子刊, PNAS, Advanced Materials, IEEE Transactions等权威期刊和会议上发表了60多篇同行评审文章。他曾获得IEEE和SIAM的多个奖项，包括IEEE信号处理学会和医学与生物工程学会的两项最佳会议论文奖，以及IEEE计算机学会的CVPR最佳论文入围奖。他是IEEE高级会员。
课题组网页: https://www.aimicroscopy.org/
We are hiring 1 research assistant. The details are listed below.
课题组现公开招聘科研助理1名；具体岗位信息如下：
Job Requirements/岗位要求:
1. Hold a degree (or to obtain a degree in 2026) in Statistics, Mathematics, Computer Science or other related areas.
2. Proficiency in Python/Matlab or other computer languages.
3. Good knowledge and strong research abilities in statistical/mathematical methodology, theory and implementation, preferable on high-dimensional data analysis, statistical models with complex structure or image processing.
4. Preference of having experience in preparing research papers or proposals in English.
5. Good communication and presentation skills in both English and Chinese.
6. This project is a collaboration between research groups from Southern University of Science and Technology and The Chinese University of Hong Kong. Specific cooperation details are to be discussed in person.
1.获得或即将获得统计、数学、计算机或其他相关学科的学位，境外名校或“985”高校相关专业硕士生优先；
2.精通Python/Matlab或其他至少一种计算机语言；
3.有较强的统计/数学方法和理论基础知识和实践能力；有高维复杂数据分析、复杂模型或图像处理研究经验者优先；
4.具有较强英文写作能力，有论文或项目书等写作经验者优先；
5.具有良好的沟通能力和展示能力；
6.本项目为南方科技大学与香港中文大学课题组项目之间的合作，具体合作方式面议。
Duties and Responsibilities/岗位职责：
1. Undertake research related to the project.
2. Help to prepare research proposals.
3. Help on other research activities.
1.进行与本课题相关的科研工作；
2.协助课题组申报各类科研课题及承担相应的科学研究任务；
3.协助完成课题组的其他日常工作。
Benefits and Rewards/待遇与福利:
For Research Assistant:
1. Monthly salary 5,000–10,000 RMB. For those with outstanding abilities, the salary is negotiable, and additional year-end performance bonuses are available;
2. Enjoy national statutory holidays and paid annual leave according to school regulations, "Five Insurances and One Housing Fund", holiday subsidies (available for major Chinese holidays, 1,000 RMB each time), monthly meal allowances, high-temperature subsidies, free medical examinations and other benefits;
3. Good space for personal growth and development. Those with excellent scientific research performance can be given priority recommendation to pursue a doctoral degree.3.
科研助理方面：
1.每月工资5000—10000元，能力出众者，薪酬可议，可额外享受年终绩效；
2.享受国家法定节假日及按学校规定的带薪年假、“五险一金”、过节费（主要中国节日都有，每次1000元）、每月餐补、高温补贴、免费体检等福利；
3.良好的个人成长与发展空间，科研表现优秀者可优先推荐攻读博士学位。
To apply/联系方式:
To apply for the position, please send the following information to Dr. Wang（wangc6@sustech.edu.cn）and Dr. Li（jzli@ee.cuhk.edu.hk）with the title “SUSTECH & CUHK JOINT RESEARCH PROJECT -RA-your name-your major”.
1. Resume (with a complete list of publications and transcripts).
2. The full manuscript of 2 representative publications.
3. Other research outputs such as books, patents, etc.
有意向者请将个人详细简历(包括成绩单和已发表文章的完整列表)、代表性学术成果等整合为一个PDF文件，邮件发送至王老师（wangc6@sustech.edu.cn ）和李老师（jzli@ee.cuhk.edu.hk）
邮件标题请注明：SUSTech & CUHK联合研究项目-科研助理-姓名-专业。
