Universitą degli studi di Pavia

 

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PhD Program Overview
In the 1st year teaching includes four mandatory courses (20 credits):

- Principles of Statistical Inference (Prof. M. Grassi) – 5 Credits
- Experimental Research Methods (Prof. R. Russo) – 5 Credits
- Behavioral Science Methods (Prof. F. Castelli) – 5 Credits
- Data Mining and Statistical Analysis with R (Prof. L. Bernardinelli) – 5 Credits

In the 2nd year, the doctorate program offers two mandatory courses for each curriculum: two mandatory courses for the Psychology and Neuroscience curriculum and two mandatory courses for the Data Science in Biomedicine curriculum, for a total of 10 credits.

Psychology and Neuroscience curriculum

- Applied Experimental Psychology (Prof. T. Vecchi) - 5 Credits
- Methods and applied techniques in Cognitive Neuroscience (Prof. A. Toraldo) - 5 Credits

Data Science in Biomedicine curriculum

- Clinical, Genetics and Molecular Epidemiology (Prof. L. Bernardinelli) - 5 Credits
- Latent Variables Models with R (Prof. M. Grassi) - 5 Credits

Optional Courses:

- Ethics of Research and Responsible Research and Innovation (Prof. G. Bottini & Dr. D. Ovadia)
- Food and Health – Mediterrasian Diet (Prof. M. Rondanelli)
- Improving our Communication Skills and Attitude in Health Care (Prof. P. Politi)
- Neuroscience of Meditation (Prof. L. Bernardinelli)

To offer a wider range of training courses the PhD has made an agreement with the doctorate in “Epidemiology, Environment and Public Health” of the University of Milan and with the doctorate in “Public Health” of the University of Milano-Bicocca.

The teaching program also includes courses from the Master in Medical and Genomic Statistics and the Master in Biostatistics and Epidemiological Methods:

1st year: Epidemiology; Basic Statistics; Medical Statistics; Genetics; Genetic Epidemiology; Genetic Statistics.
2nd year: Genetic Statistics; Genomic Statistics; Bioinformatics applied to Genetics; Casual Inference in Medicine.

PhD students refer to a personal tutor and their research progress is periodically monitored by the PhD scientific committee through oral presentations of their works in progress.

 
 
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