PhD in Data Science and Computation

• Quantitative Finance and Economics
• Materials and Industry 4.0
• Genomics and bioinformatics
• Personalised medicine
• Hardware and Infrastructure
• Machine learning and deep learning
• Computational physics
• Computational chemistry
• Big Data, Smart Cities & Society

Call for further PhD Positions
Appointed by Rectoral Decree n. 1066/2023 Prot. n. 0226313 of 04/08/2023

* The following shall take part in the work of the Examination Board as expert members for positions linked to specific research topics:

• Lorenzo Cavicchi, Alberto Rigenti - Automobili Lamborghini Spa

• Paolo Uva - Istituto Giannina Gaslini

• Maurizio Ortali - CINECA

Call for applications Appointed by Rectoral Decree n. 709/2023 Prot. n. 149534 of 02/06/2023

This course aims to train students who will be ultimately capable of carrying out academic and industrial research activities, both basic and applied, in the fields of computer sciences, data analytics, and high-performance computing. These skills may be applied to several research domains, including economy, medicine, industry 4.0, physics, chemistry, etc. In this respect, each Ph.D. student during the course is expected to produce original and significant results in terms of scientific publications and/or innovative applications, starting from expertise, which is mandatory for fully understanding such approaches and their applications. Therefore, training will be in the following basic fields: mathematics, statistics, computer science, data analysis, computational physics and chemistry, bioinformatics, etc.).

At the beginning of the course, for each PhD student a supervisor is identified who supports him/her throughout the three-year duration of the program. During the first two years of the program, the cultural background of the PhD student is expected to be integrated, expanded and deepened according to a personalised learning plan, prepared by the student in agreement with the supervisor, and communicated to the Coordinator for information. The plan foresees the achievement of at least 150 hours of courses through attendance to lectures and/or fulfilment of required final examinations, of which at least 50% must be selected from the list of courses as part of the PhD offer, and the remaining portion to be composed by supervisors’ suggestions. At the end of the first year, the “Collegio dei Docenti” (i.e. Faculty Board) approves the admission to the following year: PhD students are encouraged to have finalized a good portion of the learning plan foreseen in the first two years, although there are no requirements on this that would block the admission to the second year; the delivery of a research topic proposal for the final thesis will be required. By the end of the second year, the PhD student must have entirely completed the learning plan and must give a public presentation on the progress of the thesis work and the results achieved up to that point; based on this, the Faculty Board approves the admission to the following year. Finally, the Faculty Board decides on the admission to the final examination, based on the comments of the reviewers and any revision of the thesis. The Faculty Board may authorise a PhD student to spend periods in Italy at Universities, research centres, or companies. It is mandatory for a PhD student to spend a period of at least 3 months abroad.

During the first two years of the program, the cultural background of the PhD student is expected to be integrated, expanded and deepened according to a personalised learning plan, prepared by the student in agreement with the supervisor (the supervisors are responsible of advising the PhD students and create an adequate training plan), and communicated to the Coordinator for information. The plan foresees the achievement of at least 150 hours of courses through attendance to lectures and/or fulfilment of required final examinations (with methods to be agreed with the course's teacher), of which at least 50% must be selected from the list of courses as part of the PhD offer, and the remaining portion to be composed by supervisors’ suggestions. By the end of the second year, the PhD student must have completed the personalised learning plan and must report on the progress of the thesis. The thesis will be discussed at the end of the third and final year.

The course is the product of the collaboration of international institutes and universities in the field of data science, such as  Alma Mater Studiorum University of Bologna, Cineca, the Italian Institute of Technology and INFN. Having undergone several changes over the years, the international characteristics of the course are still being designed and developed and will emerge according to the ability of each member Faculty of professors to activate and finalize agreements for the exchange of students, both incoming and outgoing, with universities and international research institutes of high scientific and academic level. We also plan to release joint degrees in collaboration with foreign universities. The remarkable academic and scientific profile of all the members of the Faculty at an international level is evident through the indexes that measure their scientific production.

Original, relevant and significant research results are due by the end of the Course that can take different forms including for example: scientific publications, system and software design, realization and production, and any kind of  innovative applications specializing on a broad gamut of topics, such as for example: Quantitative Finance and Economics; Materials and Industry 4.0; Genomics and bioinformatics; Personalised medicine; Hardware and Infrastructure; Machine learning and deep learning; Computational chemistry & physics; Big Data, Smart Cities & Society.