PhD courses (to fulfill the 12 mandatory CFUs)

Each student must choose the courses among those listed below. The  lessons schedule will be available after the preliminary meeting of each course.
2019/2020 program lessons

ASTROPHYSICS AREA (BERTIN)

- Advanced topics in astrophysics and plasma physics-Collective phenomena in plasma physics (2 CFU-10 hours, Romé)
- Advanced topics in astrophysics and plasma physics-Fundamentals of computational fluid dynamics in astrophysics (2 CFU-10 hours, Lodato)
- Advanced topics in astrophysics and plasma physics-Cosmology (2 CFU-10 hours, Maino)
- Advanced topics in astrophysics and plasma physics-Observations of the CMB (2 CFU-10 hours,Bersanelli)
- Advanced topics in astrophysics and plasma physics-Large scale structure formation (2 CFU-10 hours, Guzzo)
- Advanced topics in astrophysics and plasma physics-Gravitational lensing (2 CFU-10 hours, Grillo)
- Advanced topics in astrophysics and plasma physics-Bayesian statistics in astronomy (2 CFU-10 hours, Lombardi)

NUCLEAR AND SUBNUCLEAR AREA (ANDREAZZA)

- Advanced topics in particle physics (4 CFU-20 hours, Andreazza, Turra, Serafini)
- Neutrino physics (2 CFU-10 hours, Vissani)
- Nuclear structure theory: Density functional methods in nuclear physics (2 CFU-10 hours, Colò)
- Nuclear structure studied with stable and radioactive beams (2 CFU-10 hours, Leoni)
- Theoretical models for heavy ion reactions around the Coulomb barrier (2 CFU-10 hours, Vitturi)
- Experimental study of transfer and fusion reactions (2 CFU-10 hours, Scarlassara)

MATTER PHYSICS AREA (CASTELLI)

- Quantum coherent phenomena (6 CFU-30 hours, Castelli, Genoni, Benedetti)
- Quantum theory of matter (6 CFU-30 hours, Onida , Manini, Parola)

THEORETICAL PHYSICS AREA (FERRERA)

- Computational, simulation and machine learning methods in high energy physics and beyond: Automated computational tools (3 CFU-15 hours, Maltoni, Zaro)
- Computational, simulation and machine learning methods in high energy physics and beyond: Monte Carlo Methods (3 CFU-15 hours, Nason)

APPLIED PHYSICS AREA (VAILATI)

- Experimental methods for the investigation of systems at the nanoscale (6 CFU-30 hours, Vailati, Paroli, Giavazzi, Zanchetta, Buscaglia, Piseri, Podestà, Cialdi, Lascialfari, Lenardi, Carpineti)

 

PhD seminars (out of mandatory CFUs)

The seminars schedule will be attached when available.

- Computational, simulation and machine methods in high energy physics and beyond: Machine Learning (3 CFU-15 hours, S.Carrazza): An introduction to machine learning techniques including model representation, parameter learning, non-linear models, hyperparameter tune, and an overview of modern deep learning strategies. The seminars will cover the theoretical and mathematical aspects of machine learning followed by practical examples of code implementation using public frameworks.