The course aims at building a scientific and professional profile enabling  the understanding of complex  biological  phenomena  and  mathematical and computer models, as well as analytical approaches to physical phenomena.

You will acquire skills from different areas: 

In the Biotechnology area, you will develop: 

• advanced skills on cellular metabolism and how it can be manipulated through genetics and metabolic engineering approaches applicable both to microbial systems and to mammalian cells.
• expertise for data -omics generation, analysis, representation and interpretation (essentially genomics and transcriptomics),
• skills for the use of complex experimental equipment and related software will be provided.

In the Information Science area, you will develop:

• computational problem solving 
• practical basis of scientific programming
• basic knowledge on biological networks and the skills to manipulate them with data integration
• expertise and knowledge to model and simulate the dynamics of biological systems
• knowledge on specific algorithms for bioinformatics applications, knowledge for the development  and implementation of bioinformatics resources
• knowledge and skills on machine learning and practical and theoretical 
• knowledge on specific data mining applications for biological systems

In the Mathematical-Physical area, you will develop: 

•  fundamental notions on statistical inference based on likelihood
• knowledge for the construction and the use of statistical models for the analysis of univariate and multivariate data, with particular reference to biomolecular data, of dynamic deterministic or stochastic models for the description of biological and biochemical phenomena
• skills to build numerical computer simulations and to recognize the potential and the limitations in the use of models
• expertise on quantum mechanics fundamental equations and on the main elements of atomic and molecular physics phenomenology
• the knowledge of the approximation methods for theoretical description of many-body systems physics, providing skills to critically evaluate molecular models limits
•  statistical mechanics fundamentals and applications of biomolecular systems, as well as  numerical techniques for the study of their thermodynamic and kinetic properties.

Teaching activities include: 

• lectures
• laboratory courses 
• seminars. 

Career Oppotunities

Graduates in Quantitative and Computational Biology will be trained to build the following professional profiles:

• Biotechnologist
• Computational Biologist
• Bioinformatics
• Biologists data and systems biology analyst