The PhD student must acquire at least 12 Mandatory Credits and develop the transversal skills offered by the University of Milan.
Courses mandatory for VAS PhD students
The PhD program in Veterinary and Livestock Sciences (VAS) has created specific required courses to equip students with the essential skills for research in veterinary and Animal Sciences.
The courses that are part of the mandatory teaching offer include:
Digital Imaging and Image Integrity in Scientific Publication: Guidelines and Standards in Basic, Veterinary and Animal Sciences (first year)
Statistical Methods Applied To Epidemiology And Animal Sciences from theory to practice (first year)
Omics Technique Applied To Veterinary and Animal Sciences (first year)
The courses included in the elective teaching offer provided by the VAS doctorate are:
Cell and Tissue Culture: from Basic Principles to Advanced Technologies
Non-invasive biomarkes for the future research designs
Pathology of Laboratory Animals
The Animal Microbiome: Basic Concepts for Veterinary Medicine and Animal Productions
The future of mesenchymal stem cells: lessons from the past and interpretations of the present
Students can also include courses from other doctorales listed in the “Course catalogue ” section.
Soft skills
PhD students must attend soft skills courses organized by the University of Milan, totaling 72 hours to be completed within the three years of the program. Starting in 2024, a skills week has been introduced, offering three time slots during the academic years to meet the approximately 24 hours per year recommended. Students are required to partecipate in one week annually, with the option to supplement or substitute some soft skill courses with the Open Sciences 4EU+ seminars. More details are available on the university web page (link).
How to enrol in the mandatory courses for VAS PhD students
To enroll, you must log in to the webpage link using your university credentials.
The enrollment deadline for courses is usually set for the 25th day of the month prior to the start date.
