Transferable skills

Scientific writing and presentation course with final assessment.
Through in-class exercises, small group discussion, and out-of-class homework, PhD students will learn to publish results in scientific journals, identify components of a manuscript, write with clarity, deal with peer-reviews and debate results, prepare and deliver effective presentations.

Statistical data processing laboratory with final assessment.
Through a combination of lectures, computer-based exercises and workgroups, PhD students will gain an understanding of how to deal with common issues in the analysis of real world biological data such as heterogeneity of variance, and spatial and temporal non-independence.
Particular attention will be given to the analysis of big-data produced by high-throughput approaches (e.g., metagenomics, genomics, transcriptomics).
The students will become familiar with cutting-edge techniques, data mining, handling and analysis, learning to design effectiveexperiments. Hands on computer tutorials will allow students to apply statistical models -
using state-of-the-art tools - to real data, collected by researchers to answer real biological questions.

The Research and Third Mission Division of the University, in collaboration with professors and experts in these fields, will organize a course on "systems and funding opportunities for research at national and international levels".
In particular, PhD students will learn to identify key funding EU programmes (H2020, Erasmus+) and learn to prepare a grant proposal outline and basic aspects of project implementation (funding principles, grant/internal agreements, budgeting, project monitoring, review).

The Research and Third Mission Division of the University, in collaboration with professors and experts in these fields, will organize courses on "Protecting and enhancing research results and intellectual property".