PhD in Statistics and Machine Learning
PhD Program Officer
The PhD in Statistics and Machine Learning at Bocconi University is a rigorous, internationally oriented four-year doctoral program taught in English. It provides in-depth training in modern Statistics and Machine Learning, with strong foundations in probability and an emphasis on integrating theory, modeling and computation.
The program's overarching objective is to train researchers to make original contributions at the highest international level.
Program Structure and Training
The program features two years of structured coursework, following the model of leading US PhD programs. This substantial coursework component provides students from different backgrounds with a common foundation. Research begins during the second year and becomes the main focus of the third and fourth years.
The first year comprises 12 courses providing rigorous foundational training in Statistics, Probability and Machine Learning, and concludes with the Summer School in Advanced Statistics and Probability.
The second year offers nine research-oriented courses focusing on advanced topics and recent developments in Statistics and Machine Learning, including one taught by a distinguished visiting professor. A research reading group complements these courses. Students also begin working on research problems, develop their research interests and identify an advisor.
The third and fourth years are devoted to original research and the completion of the doctoral dissertation, with close faculty supervision.
For the complete study plan, please see the Courses and Requirements page.
Faculty and Research Environment
The faculty includes internationally renowned researchers with strong publication records in leading academic outlets. Their expertise spans Bayesian statistics, machine learning, nonparametric and high-dimensional inference, computational methods and algorithms, and applied probability. Applications range from complex networks and neuroscience to genomics, biomedicine, climate extremes and ecological risk.
Students become part of Bocconi's active international research community, with opportunities to interact with distinguished visiting scholars and attend the Statistics seminar series and seminars organized by the Bocconi Institute for Data Science and Analytics (BIDSA). The research environment also includes the Bayesian Learning Laboratory (BayesLab), a research unit within BIDSA that brings together faculty, postdoctoral researchers and students interested in Bayesian methods in Statistics and Machine Learning.
Students are also encouraged to present their work at international conferences and have opportunities to spend research periods abroad.
Further information about the researchers involved in the program is available on the Faculty page.
Career Opportunities and Placement
The program prepares students for research careers in academia as well as in industry and public organizations.
The PhD in Statistics and Machine Learning builds on Bocconi's longstanding tradition in Statistics, dating back to the University's foundation, and is a natural evolution of its PhD in Statistics, established in 2001 and subsequently expanded into the PhD in Statistics and Computer Science.
Past graduates in this area have secured positions at leading universities and research institutions worldwide, including Duke University, Harvard University, Stanford University, the University of Texas at Austin, the University of Cambridge, the University of Oxford, the University of Warwick and EPFL. Others have pursued careers in industry and public organizations, including Google, Bending Spoons, the European Central Bank and the Bank of Italy.
For the complete historical placement record, please see the Placement page.
Admissions and Funding
We welcome applications from highly qualified and motivated candidates with backgrounds in Statistics, Mathematics, Data Science, Computer Science, Economics, Engineering and other quantitatively oriented fields.
The program offers six four-year fellowships fully funded by the Tech Europe Foundation (TEF). Each fellowship provides €27,000 gross per year and a full tuition-fee exemption.
The first cohort will begin in September 2027. Applications close on 8 February 2027. For eligibility requirements, application procedures and selection criteria, please consult the PhD Admissions page.