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Call for AICS - Partnership for Knowledge project In the area of Sustainable Energy, Environment and Industrial Innovation

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.

Graduates will be trained as experts in the field of Quantitative and Computational Biology with particular relevance to the biomedical field.

Skills will be acquired in the following areas:

biotechnology area

with the objective of:

  • providing 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.
  • providing expertise for data -omics generation, analysis, representation and interpretation (essentially genomics and transcriptomics),
  • providing skills for the use of complex experimental equipment and related software will be provided.

information science area 

with the objective of:

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

mathematical-physical area 

with the objective of:

  • introducing fundamental notions on statistical inference based on likelihood, 
  • providing 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,
  • providing skills to build numerical computer simulations and to recognize the potential and the limitations in the use of models, 
  • providing expertise on quantum mechanics fundamental equations and on the main elements of atomic and molecular physics phenomenology, 
  • introducing students to the approximation methods for theoretical description of many-body systems physics, providing skills to critically evaluate molecular models limits,
  • providing concepts on statistical mechanics fundamentals and applications of biomolecular systems, as well as  numerical techniques for the study of their thermodynamic and kinetic properties.