| Code | Bologna |
|---|---|
| Academic Year | 2019-2020 |
| Subject area | Mathematical Physical, Chemical and Astronomical Sciences |
| Cycle | 35 |
| Coordinator | Prof. Andrea Cavalli |
| Language | English, Italian |
| Duration | 4 years |
| Positions | 15 positions. More information in the PhD Programme Table |
| Application deadline | May 15, 2019 at 01:00 PM (Expired) |
| Enrolment period | From Aug 01, 2019 to Aug 26, 2019 |
| Doctoral programme start date | Nov 01, 2019 |
- Operating centre
- Bologna
- Main Department
-
Department of Computer Science and Engineering - DISI
- Associated Departments
-
Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" - DEI
- Associated locations (agreements)
- Politecnico di Milano
Fondazione Golinelli
Fondazione Istituto Italiano di Tecnologia
Istituto Nazionale di Fisica Nucleare - Mobility abroad
- Yes (3 months)
- Research topics
- Quantitative Finance and Economics
- Materials and Industry 4.0
- Genomics and bioinformatics
- Personalised medicine
- Hardware and Infrastructure
- Machine learning and deep learning
- Computational physics
- Big Data, Smart Cities & Society- Job opportunities and potential areas of employment
- This course builds upon fundamental data science disciplines to train candidates that should to become able to carry out academic and industrial research at a higher level of abstraction, with different final specializations in several different fields where data analysis and computation becomes prominent. The principal career opportunities include, but are not limited to: academic career; research activities for industries or institutions; management companies and organizations where data manipulation need an analytic as well scientific approach.
- Admission Board
-
Surname Name Institution Role e-mail Cavalli Andrea Università di Bologna member andrea.cavalli@unibo.it De Vivo Marco Istituto Italiano di Tecnologia member marco.devivo@iit.it Orsenigo Carlotta Politecnico di Milano member carlotta.orsenigo@polimi.it Roccetti Marco Università di Bologna member marco.roccetti@unibo.it Grandi Claudio INFN representative of financing body claudio.grandi@bo.infn.it Baresi Luciano Politecnico di Milano substitute luciano.baresi@polimi.it Benini Luca Università di Bologna substitute luca.benini@unibo.it Rocchia Walter Istituto Italiano di Tecnologia substitute walter.rocchia@iit.it Zoccoli Antonio Università di Bologna substitute antonio.zoccoli@unibo.it
- Learning outcomes
- This course aims at being "special" in the sense that it should train people to become able to carry out academic and industrial research at a level of abstraction that builds atop each single scientific skill which lies at the basis of the field of "data science". Drawing on this, each ph.d. student should produce original and significant researches in terms of scientific publications and innovative applications, blending basic disciplines, such as for example: mathematics, statistics, computer science, computational sciences ..., and finally specializing in specific fields 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 physics; Big Data, Smart Cities & Society.
- Activities to be carried out by Doctoral candidates
- 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 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. The admission (from the first) to the second is taken into consideration by the Board (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 Board (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 Board (and approved in the positive case) on the basis of a candidate's public presentation regarding the current status of his/her thesis. The Board 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.
- Research training activities compliant with the Doctoral programme's learning outcomes
- 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).
- Internationalization features
- This Ph. D Course starts off based on a joint collaboration of the University of Bologna with politecnico di Milano, the Golinelli Foundation, the Italian Institute of Technology, Cineca, the ISI Foundation and INFN. Even though they are all Italian, each of the aforementioned institutions has already achieved a renown international role in the upcoming field of scientific management and processing of data. Nonetheless, as a new Course we are going to discuss, design and establish a series of international initiatives that include the possibility to reach agreements with foreign Universities and Research Institutions to issue, for example: joint doctoral degrees, cotutorships and student exchanges. These activities will be carried out also based on the contribution that each member of the Course Board will provide.
- Expected research results and products
- 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 physics; Big Data, Smart Cities & Society.
- Doctoral programme Academic Board
Surname
Name
University/Institution
Qualification
AGASITI
TOMMASO
Politecnico di Milano
Professore Associato
BARESI
LUCIANO
Politecnico di Milano
Professore Ordinario
BAZZANI
ARMANDO
Università di Bologna
Professore Associato
BENINI
LUCA
Università di Bologna
Professore Ordinario
BRAMBILLA
MARCO
Politecnico di Milano
Professore Associato
CAPRIOTTI
EMIDIO
Università di Bologna
Ricercatore
CAVALLI
ANDREA
Università di Bologna
Professore Ordinario
CIARLETTA
PASQUALE
Politecnico di Milano
Professore Associato
DE VIVO
MARCO
Istituto Italiano di Tecnologia
Primo ricercatore
GRANDI
CLAUDIO
INFN
Dirigente tecnologo
GUGLIELMI
ALESSANDRA
Politecnico di Milano
Professore Ordinario
ORSENIGO
CARLOTTA
Politecnico di Milano
Ricercatore
PANZERI
STEFANO
Istituto Italiano di Tecnologia
Primo ricercatore
PRAROLO
GIOVANNI
Università di Bologna
Professore Associato
RESTELLI
MARCELLO
Politecnico di Milano
Ricercatore
ROCCETTI
MARCO
Università di Bologna
Professore Ordinario
SARTORI
LAURA
Università di Bologna
Professore Associato
SCIUTO
DONATELLA
Politecnico di Milano
Professore Ordinario
SERI
MARCO
Università di Bologna
Professore Ordinario
ZERBETTO
FRANCESCO
Università di Bologna
Professore Ordinario
ZOCCOLI
ANTONIO
Università di Bologna
Professore Ordinario
Notices
Evaluation sub criteria
Final ranking list
See also
- AMS phD thesis (in Italian) Published
Alumni