PhD in Statistics and Computer Science

Bocconi University in Milan, founded in 1902, is an internationally respected institution for economics, management and finance. Its compact urban setting and research-led faculty create a learning environment that balances analytical rigor with practical application. With around 15,200 students and roughly 4,000 internationals, Bocconi fosters cross-cultural collaboration and a global perspective that suits students aiming for careers in business, public policy and finance.

Academic offerings span undergraduate, graduate and executive programs, including 27 specialized tracks that emphasize quantitative skills, case-based learning and industry engagement. Courses are frequently complemented by internships, consulting projects and career workshops supported by the university’s strong corporate partnerships. Research centers and visiting practitioners bring current market insights into the classroom, while entrepreneurship initiatives encourage students to develop real ventures during their studies.

Student life in Milan adds cultural and professional depth: the city’s commercial and creative industries provide internship pipelines, networking events and cultural enrichment. Bocconi’s career services, alumni network and recruiting calendar help students transition smoothly into employment across Europe and beyond. International students benefit from orientation, language support and active student associations, making Bocconi a focused choice for those seeking an applied, internationally connected education in economics and business.

The PhD in Statistics and Computer Science at Bocconi University is a 4-year doctoral program for talented students who want to gain strong mathematical, statistical, computational and programming backgrounds. This program is for students with a Master's degree who want to stand out in their field. The program's main advantage is its cross-disciplinary nature.

The curriculum helps students develop skills in statistical methodologies, computational algorithms, and probabilistic modeling. Students learn about machine learning, data science, and theoretical computer science. The program includes hands-on components to help students gain practical experience.

Graduates of this program can work as data scientists, statistical analysts, computer science researchers, or machine learning engineers. They can work in academic institutions, research organizations, or industry. Some potential employers include tech companies, financial institutions, or government agencies.