Education and Employment:

Awards and Honors:

Seminars

[English] 北大-上交对撞机物理联合青年论坛（京沪云坛）：Double Higgs search in all-hadronic final states (4 b-jets) at ATLAS and towards Higgs self-coupling measurement

[中文] 北京大学高能物理研究中心学术讲座：Machine learning in high energy physics (with a focus on the LHC)

[中文] 江苏省青年物理学家论坛：深度学习在高能物理实验中的应用

I am actively involved in the ATLAS experiment at the Large Hadron Collider (LHC) located at CERN in Geneva, Switzerland, and in the BESIII experiement at Beijing Electron–Positron Collider. My research focuses on experimental data processing and physical analysis, the application of machine learning and quantum machine learning, and the development of detector technologies. I am seeking to recruit 1-3 master's and doctoral students each year, and I also offer research internship opportunities for junior undergraduate students. I warmly welcome students with a strong interest in particle physics experiments to reach out! Additionally, I am continuously open for postdoctoral applications with strong ATLAS Higgs analysis background. Feel free to reach out to me at rui.zhang(AT)nju.edu.cn. [中文版]

International students with background with LHC analysis or quantum machine learning are welcome to apply for PhD degree after having a master degree. Chinese is required (HSK level-4, grade > 180). The application is through the China Scholarship Council. More information is available on University's Institute for International Students [link] or the CSC website [link]. The deadline is usually in January, therefore please contact me in October-December or earlier. You expect to finish the following two sets of tests before contacting me: test1, test2 (replace nju to box.nju in the url).

For a short visit, students are welcome to apply for the Grip program in China [link]. The application opens from January to March every year. Please contact me in October-December or earlier to express your interest and motivation.

Research field to work in my group includes:

- Data analysis at ATLAS (only for Ph.D);

- Machine learning application in High Energy Physics data analysis (for Ph.D and Grip);

- Quantum machine learning application in High Energy Physics data analysis (for Ph.D and Grip).