Call for Applications
The PhD in Statistics and Machine Learning at Bocconi University is a rigorous, internationally oriented four-year doctoral program taught in English, the working language of Bocconi's international research community. It provides in-depth training in modern Statistics and Machine Learning, with strong foundations in probability and an emphasis on integrating theory, statistical modeling, and computation.
The program features two years of structured coursework, following the model of leading US PhD programs. The first year provides rigorous foundational training in Statistics, Probability, and Machine Learning, and concludes with the Summer School in Advanced Statistics and Probability. The second year offers specialized, research-oriented courses focusing on advanced topics and recent developments in the field. Alongside this coursework, students begin working on original 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.
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. Students also have opportunities to interact with distinguished visiting professors, attend Statistics seminars and seminars organized by the Bocconi Institute for Data Science and Analytics (BIDSA), participate in international conferences, and spend research periods abroad.
The program's overarching objective is to train researchers capable of making original contributions at the highest international level. It prepares students for research careers in academia as well as in industry and public organizations. The program 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. Graduates of the PhD in Statistics have secured positions worldwide at leading universities and research institutions, as well as in major public and private organizations.
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.
QUALIFICATIONS:
Applications can be submitted by candidates of any citizenship who:
The PhD School offers a maximum of 6 places with a fellowship fully funded by Tech Europe Foundation (TEF).
Fellowships amount to € 27,000 gross per year for each of the four years. Students with fellowship are exempt from the payment of tuition fees for the duration of the four-year program.
The PhD School also offers 1 place with payment of tuition fees which amount to € 15,000 per year for years 1 and 2 and € 5,000 per year in years 3 and 4 and 1 place with full tuition waiver.
For more detailed information, please see the full official call published on the website by clicking the Apply button above.
For more detailed information about our program, please visit the website here.
APPLICATION PROCEDURE:
To apply for our PhD program, only our online application procedure may be used.
Applications are due by 8 February 2027.
The assessment of the applicant is based on:
A minimum of 60 total points out of 100 is required to be eligible for admission to the program.
Please consult our website for complete details of our application procedure. Click the Apply button above to access.
For more information about the program, please feel free to contact phdadmission@unibocconi.it or the PhD Director, Professor Igor Prünster (igor.pruenster@unibocconi.it).
| Qualification Type: | PhD |
|---|---|
| Location: | Milan - Italy |
| Funding for: | UK Students, EU Students, International Students |
| Funding amount: |
€27,000
£23,484.49 converted salary* gross per year for each of the four years |
| Hours: | Full Time |
| Placed On: | 3rd November 2026 |
| Closes: | 8th February 2027 |
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