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

NRPP Call Admission Board
Appointed by RD 1103/2022 Prot. n. 0162873 of 17/07/2022

Call for Application Admission Board
Appointed by RD 830/2022 Prot. n. 0127511 of 30/05/2022

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 each student is supported by a supervisor, member of the Collegio dei Docenti (Faculty Board), who guides him throughout the Ph.D. studies. The first 24 months are devoted to the integration and deepening of the student expertise, according to a personalized learning plan (drawn up by the student in agreement with the supervisor and then submitted to the PhD Faculty for approval). The learning plan foresees reaching 40 CFU (credits) by attending courses and passing the corresponding exams. By the 20th month (from the beginning of the course) the student must submit a written thesis proposal to the Board for approval. By the end of the 24th month the student must have completed the personalized learning plan and must report on the progress of the thesis draft. The admission (from the first) to the second is taken into consideration by the PhD Faculty (and approved in the positive case) on the basis of the fact that the candidate has obtained an adequate number of CFU. The admission (from the second) to the third is is taken into consideration by the Faculty (and approved in the positive case) if the candidate has obtained all the  CFU and on the basis of a candidate's public presentation regarding his/her thesis proposal. The third and the fourth years are entirely devoted to the thesis work. he admission (from the third) to the fourth is is taken into consideration by the Faculty (and approved in the positive case)  on the basis of a candidate's public presentation regarding the current status of his/her thesis. The PhD Faculty finally approves the admission to the final exam, on the basis of the reviewers' comments. The Board may authorize a student to spend a period in Italy at universities, research centers or companies. It is mandatory for the student to spend a period of at least 3 months abroad, during the 3rd/4th year of the course.

At the beginning of the course each student is supported by a supervisor, either a member of the Collegio dei Docenti (Faculty Board) or an external one upon the confirmation by means of one of the Members of the Collegio, who guides him throughout the Ph.D. studies. The first 24 months are devoted to the integration and deepening of the student expertise, according to a personalized learning plan (drawn up by the student in agreement with the supervisor and then submitted to the Board for approval). The learning plan foresees reaching 40 CFU (credits) by attending courses and passing the corresponding exams. By the 20th month (from the beginning of the course) the student must submit a written thesis proposal to the Board for approval. By the end of the 24th month the student must have completed the personalized learning plan and must report on the progress of the thesis draft. A further assessment of thesis is scheduled by the end of the third year. Finally, the thesis will be discussed and defended at the end of the Ph.D. course (end fourth 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.