Course catalogue
Create your own master’s programme by choosing between the different specializations of our partner universities.
Academic Programme
Implemented from September 2025
Data Science and Applications to Chemistry (3 ECTS)
All courses during this semester
- Experimental methods on innovative research infrastructures - 5 ECTS
- Digital Micro-certification "The challenges of sustainable chemistry" - 10h
- Transferable skills : French language & interculturality (3 ECTS)
- Quantum mechanics towars quantum computing (5 ECTS)
- Winter school in Data Science (2 ECTS)
- Organic / Inorganic chemistry towards sustainability (5 ECTS)
- Kinetics and Electrochemistry (5 ECTS)
- Introduction to biophysics and microscopies for life science (5 ECTS)
All courses during this semester
- Luminescence spectroscopy of Lanthanides (3 ECTS)
- Summer School in Entrepreneurship (5 ECTS)
- Transferable skills: Polish course (3 ECTS)
- The molecules of life: from structure to chemical function (5 ECTS)
- Thermodynamics and soft matter (3 ECTS)
- Introduction to solid state (5 ECTS)
- Tech-infused perspectives on photochemical reaction dynamics (6 ECTS)
- Transferable skills: Portuguese course (3 ECTS)
- Summer School in Entrepreneurship (5 ECTS)
- Solid State Physics (5 ECTS)
- Molecular Energetics (3 ECTS)
- Laboratory of Materials and Surface Analysis (5 ECTS)
- Interfacial Electrochemistry (3 ECTS)
- Interfaces, Colloids and Self-Assembly (6 ECTS)
All courses during this semester
- 1-year research project - master thesis (equivalent 45 ECTS)
- Progress assessment of the research project (equivalent 6 ECTS)
- Weekly seminars (equivalent 4 ECTS)
- Special Topics in Chemistry (equivalent 5 ECTS)
- French language courses (3 ECTS)
- Nanosciences (6 ECTS)
- Medical applications of nanomaterials and radiations (6 ECTS)
- Top management, corporate law, and project writing for technology transfer and decision making (4 ECTS)
- Tracking ultrafast radiation-induced reactivity (3 ECTS)
- Applications for renewable energy and storage: solar fuels, batteries and hydrogen (6 ECTS) (6 ECTS)
- Scientific Writing and career objectives (2 ECTS)
- Surface Science and Nanostructuring at Surfaces (6 ECTS)
- Polymers for electronics and energy harvesting (5 ECTS)
- Electrochemical systems for fuel and electrolysis cells and batteries (6 ECTS)
- Project-based laboratory on device building (3 ECTS)
- Italian Courses (3 ECTS)
- Chemistry and Technology of Catalysis (5 ECTS)
Content
Computational tools: harmonizing competences (8 hours)
- Basics of numerical analysis (2 hours)
- Basics of Bayesian theory (3 hours)
- Basics of regularization theory (3 hours)
Artificial Intelligence: the many aspects of data modeling (10 hrs)
- Numerical Simulation (2 hours)
- Inverse Problems (4 hours)
- Machine Learning (4 hours)
Applications to chemical and biochemical data (6 hrs)
- STM imaging (2 hrs)
- Tracer kinetics (2 hrs)
- Chemical Reaction Networks (2 hrs)
Aims
The general objective of the course is to provide students with a first overview of the main issues related to modern data science and its cultural background. The course has also two more specific objectives. The first one is to illustrate some computational tools representing the methodological basis for any artificial intelligence approach to data analysis problems. The second one is to describe three applications concerned with the use of data science methods in chemistry and biochemistry: the problem of the automatic recognition and classification of atomic species in Scanning Tunnelling Microscopy; the modelling of glucose metabolism by means of nuclear medicine data; the simulation of the chemical reaction network at the basis of a specific cellular transition in oncogenesis.
Pre-requiste
Students attending the course should know in advance the basics of
- Linear Algebra (vectors, matrices and their norms; linear systems; inversion of a matrix; eigenvalues)
- Calculus (properties of functions; limits and continuity; differentiation and integration)
Teaching Staff
Michele Piana, Dipartimento di Matematica, Università di Genova
Hours
24 (lectures)
Grading System
20% homework
80% oral presentation
mid-term exam: no
final-exam: yes