PhD Training Project

The Teaching Board approves the training project for each PhD student.

The PhD student’s training project consists of:

  • developing an individual research program referring to a specific disciplinary field among those on which the Course is focused, under the guidance of the Supervisor;

  • attending teaching activities at doctoral level complementary to the research not lower than 20 CFU. The recognition of the CFU, which can be acquired by attending courses and other educational activities, is carried out by the Teaching Board which authorizes the attendance and assesses the results. Educational activities, which can also be organized in common between more than one PhD course, also include training activities aimed at supporting research activities and providing tools to outline the professional identity of future research doctors.

The PhD course in Computer Science, Mathematics and Physics sets out the acquisition of

At least 12 CFU
  • with attendance (and passing possible final tests) of specialist courses in the area and in the related discipline, chosen among those scheduled annually by the Teaching Board. The “PhD Studies Manifesto” highlights the courses planned for the academic year and specifies the credits for each
  • with attendance (and passing possible final tests) of specialist courses in the area and in the related discipline, organized by other universities / research institutes / companies. The Teaching Board assesses the suitability of these activities with respect to the student’s training and research objectives and establishes the number of credits to be awarded.
At least 2 CFU
  • with attendance (and passing possible final tests) of Cross-cutting activities courses / seminars, chosen among those scheduled annually by the Research Services Area in the Cognitive and interpersonal, Career development, Communication, Mobility, and Research areas. The courses planned for the current year, with indication of the credits assigned, are available at link https://www.uniud.it/it/ricerca/lavorare-nella-ricerca/
  • with attendance (and passing possible final tests) of courses / seminars / conferences organized by the University. The Teaching Board assesses the suitability of these activities with respect to the student’s training and research objectives and establishes the number of credits to be awarded
  • with attendance (and passing possible final tests) of Cross-cutting activities courses organized by other universities / research entities / companies. The Teaching Board assesses the suitability of these activities with respect to the student’s training and research objectives and establishes the number of credits to be awarded.

The individual research program ends with the writing of the thesis. The thesis, written in English, must contribute to the advancement of knowledge or methodologies in the chosen field of investigation.

The Teaching Board annually evaluates the training and research activities carried out by each PhD student for the admission in the following year and to the thesis assessment stage.

Courses

Starting from 2021-2022 the courses offered for this PhD program are the union of the courses offered for the programs in Computer Science and Artificial Inteligence and in Mathematical and Physical Sciences.

Basic courses:

Advanced courses:

Graduate students can also attend selected courses of the master programs in Computer Science, Mathematics, and Multimedia, Communication and Information Technology.

In addition, the courses of the Scuola Superiore (School for Advanced Studies of the University of Udine) are open to PhD students.

Basic courses:

  • An introduction to dynamical systems and the theory of deterministic chaos, Lecturer: Fabio Zanolin (DMIF), SSD MAT/05, 2 CFU attendance + 2 CFU homework, March-April 2020, 8 hours, board contact: Fabio Zanolin (held online in May-June)
  • Spectral analysis, Fourier transform, and applications, Lecturer: Carlo Drioli (DMIF), SSD INF/01, 2 CFU attendance + 2 CFU homework, May 2020, 8 hours, board contact: Alberto Marcone (held online in June)
  • Machine and Deep Learning for Natural Language Processing, Lecturer: Giuseppe Serra (DMIF), SSD INF/01, 4 CFU attendance + 2 CFU homework, June-July or September 2020, 20 hours, board contact: Giuseppe Serra (held online in September)

Advanced courses:

  • Matrices, graphs, consensus, Lecturer: Enrico Bozzo (DMIF), SSD MAT/08, 2 CFU attendance + 2 CFU homework, January-February 2020, 8 hours, board contact: Fabio Zanolin (started in March and completed online in July)
  • Data Science, the baseline for cross-disciplinary research, Lecturer: Massimo Brescia (INAF – Capodimonte Astronomical Obs.), SSD FIS/01, 3 CFU attendance + 2 CFU homework, March 10-13, 2020, 15 hours, board contact: Andrea Vacchi (held online in April and May)
  • Generalized Descriptive Set Theory, Lecturer: Vincenzo Dimonte (DMIF), SSD MAT/01, 2 CFU attendance + 2 CFU homework, June 2020, 10 hours, board contact: Alberto Marcone (held online in June)
  • Reverse Mathematics of Combinatorial Principles, Lecturer: Damir Dzhafarov, (University of Connecticut, USA), SSD MAT/01, 2 CFU attendance + 2 CFU homework, July 20-31, 2020, 10 hours, board contact: Alberto Marcone (held online in July)

Graduate students can also attend selected courses of the master programs in Computer Science, Mathematics, and Multimedia, Communication and Information Technology.

In addition, the courses of the Scuola Superiore (School for Advanced Studies of the University of Udine) are open to PhD students.

Teaching Activities:

  • ZZ-Structures: an alternative computer universe (SSD INF/01), lecturer: Antonina Dattolo (DMIF) 
  • Teoria descrittiva degli insiemi, Assioma di determinatezza e Grandi cardinali (SSD MAT/01), lecturers: Alberto Marcone, Vincenzo Dimonte (DMIF)
  • Bisumulation and Simulation: Algorithms and Applications (SSD INF/01), lecturers: Alberto Policriti, Carla Piazza (DMIF)

Additional Teaching Activities:

  • Constraint Programming (SSD INF/01), lecturer: Agostino Dovier (DMIF)
  • Automated Reasoning (SSD INF/01), lecturer: Agostino Dovier (DMIF)
  • Applied Dynamical Systems (SSD MAT/08), lecturer: Dimitri Breda (DMIF)
  • Teoria qualitativa dei sistemi dinamici,(SSD MAT/05), lecturer: Fabio Zanolin (DMIF) 
  • Teoria degli insiemi (SSD MAT/01), lecturer: Alberto Marcone (DMIF) 

Advanced Teaching Activities:

  • Computable Analysis (SSD MAT/01), lecturer: Vasco Brattka (Universität der Bundeswehr München)
  • On transitivity and Devaney’s chaos: autonomous and nonautonomous discrete dynamical systems (SSD MAT/02), lecturer: Manuel Sanchis López (Universitat Jaume I)
  • Software Configuration Management (SSDINF/01), lecturer: Lars Bendix (Lund Institute of Technology, Sweden)