PhD in Psychology Neuroscience and Data Science
PhD Program

Psycology and Neurosience XXXVII Cycle

The PhD course

Within the doctoral course there is a compulsory structured educational-training program for all doctoral students, organized into 6 courses (4 courses for the first year and 2 courses for the second) specially organized by teachers belonging to the teaching staff as responsible (see the “Didactic Activity” sheet for a detailed description of the courses).

For the first year, the teaching activities are common to the two curricula, for the second year, 2 courses common to the psychological curricula (Psychology and Neuroscience curriculum) and 2 common to the medical curricula (curriculum in Data Science in Biomedicine). In this way, we want to guarantee doctoral students an optimal basic training in the methodological and statistical fields in the initial stages of their training and then focus more on the issues of the reference discipline and the research project they have undertaken.

For each of the three years of PhD, other didactic activities are also planned according to the possible training itineraries for subgroups of PhD students; they are often connected with the presence in the departments, universities and foundations with which the doctorate has conventions and research collaborations of foreign or Italian teachers of high international level.

A part of this activity is also carried out in the context of the School of Advanced Doctoral Training, in which common seminars are organized, such as genetic statistics seminars and reset courses in statistics and epidemiology. This activity, although limited to areas of a common nature to the various doctorates that are part of the School itself, favors the scientific-methodological exchange, the comparison between close experiences and the development of a common evaluation standard.

Lastly, the training of doctoral students is supported through the encouragement to participate in tenders for scholarships to attend summer schools present on the national and international territory and is completed through scientific collaborations with Italian and foreign researchers belonging to universities and foundations with which the doctorate has collaborations and conventions and through stays and internships at Italian and foreign research structures.

Form for the attribution of training credits (CFU)

 

Year

Total

 

1st year

2nd year

3rd year

 

Mandatory courses

20

10

0

30

Conferences/Seminars/Schools

4

4

0

8

Research activities

36

46

40

122

PhD thesis writing

0

0

20

20

 

 

 

 

 

Total (CFU)

60

60

60

180

Credits (CFU: Credito Formativo Universitario)
1 hour = ¼ di credit

Department Office


Via Bassi, 21
27100 Pavia (Italia)
Email: dbbs.segreteria@unipv.it
Phone: 390382987005

Education Director Office


Piazza Botta 11 – 27100 Pavia, Italy
Email: gabriella.bottini@unipv.it
Phone: +39 0382 986453

Research and Third Mission Unit – PhD office


Via Ferrata n. 5 – Pavia, Italy

Office page

Student Resources

Courses

1st Year Mandatory Courses

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2nd Year Mandatory Courses

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Optional Courses

Nutrition and physical activity for health and well-being: let’s debunk fake news with scientific evidence

Credit : 6 Credits
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Food and Health: mediterrasian diet

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Data mining and data analysis with R

Credit : 5 Credits
More Detail

Research Areas

  1. Behavioral, neurophysiological and anatomical correlates of cognitive processes and emotions in normal subjects and patients with neurological and psychiatric diseases (G. Bottini, A. Toraldo, M. Gandola).
  2. How neurostimulation (TMS), cognitive and metacognitive trainings focused on working memory updating or theory of mind affect sensory, cognitive and socio-cognitive behavior in lifespan (T. Vecchi, P. Palladino, E. Cavallini).
  3. Promoting attachment, emotion regulation, socioemotional learning and theory of mind in typical and atypical subjects across life span (L. Barone, S. Lecce, A. Zanetti).
  4. Occupational well-being and psycho-social risk factors (P. Argentero, I. Setti).

How to apply to the Data Science in Biomedicine Course