Programme Structure and Funding
The project is a full-time doctoral programme and is based on the following:5Year. School fees100,000RMB/year, total tuition fees and related costs About500,000RMB/year. Spring enrolment, previous year10Month1Deadline for application (full award). Autumn admission, application for scholarships11Month14No applications for scholarships12Month15End of day application.
Entry Requirements
Academic background: A bachelor’s or master’s degree in computer science or a related discipline. Minimum GPA: 3.2/4.0 for fall entry and 3.6/4.0 for spring entry. Language requirements: TOEFL of at least 79, with no section below 19; or IELTS of at least 7.0. Applicants who hold a degree from an English-speaking country may be exempt from the language requirement.
Application Materials
- Academic curriculum vitae (not more than two pages)
- Three letters of recommendation (submitted online by the proposer)
- Certificate and report card
- Language report card
- Study proposals
Application Period
Spring: 8 1 - 8 31; fall: 10 1 12 15
Career Prospects
Under the mentor ’ s system, Ph.D. students will have in-depth knowledge of algorithm design, computer system architecture, artificial intelligence and machine learning, data analysis, software engineering and system development methods, and comprehensive scientific capabilities across the fields of computer science, engineering, information science and applications. Graduates have broad development prospects in the following areas:
• Scientific institutions and laboratories: research, system development, algorithm optimization and technology conversion in front-line computing techniques at national or international research centres, laboratories and industrial research and development institutions. • Science and technology enterprises and innovation entrepreneurship: jobs in research and development, product design, system architecture, data analysis and technological innovation in software development companies, artificial intelligence enterprises, cloud computing and big data platforms, medical information and financial technology companies.
• Computer Data and Smart System positions: algorithm development, system optimization, data modelling and intelligent decision-making support for positions related to data science, artificial intelligence applications, machine learning engineering, network security, intelligent manufacturing and high performance computing. Through systematic academic training and interdisciplinary research, Ph.D. students will acquire a solid theoretical foundation, experimental skills and data analysis capacity in computer science and engineering, develop independent scientific thinking, technological innovation and interdisciplinary cooperation, and lay a solid foundation for future development in the fields of academic, scientific, industrial and technological innovation.
