Second cycle degree in

Physics of data (2020/2021)

Class: LM-17 - Physics

Class LM-17 - Physics
Duration 2 years
Branch Padova
Language English
Tuition fees and scholarships
Access Open access with admission requirements
Reference structures Department of physics and astronomy, Scuola di scienze

Next Call for applications (international students):

  • 7th April-7th June: non-EU applicants residing outside Italy
  • 7th April-7th July: EU applicants or equivalent

Developing fundamental methods and techniques for Big Data analysis to face the challenges that the digital revolution has brought to our society: these are the goals of the course, which trains a new generation of physicists, capable of combining advanced knowledge in physics with high-level training in the new data science. While physics aims at interpreting natural phenomena whose complexity requires the collection, management and analysis of large amounts of data, the need to train professionals who also know how to develop methods and techniques for such analysis is growing. As a "data physicist" you will have advanced training in physics, mathematics and computer and calculation techniques, you may find employment in many different contexts, such as academic institutions, research centers, digital and consulting market companies, start-ups and high-tech industries.

  Deepening

Characteristics and objectives
The program intends to build an academic and professional figure that combines advanced knowledge in the field of Physics with a high-level training in Data Science.
The modeling and the theoretical interpretation of complex natural phenomena from large amounts of data are at the core of the research in Physics. The Big Data revolution presents in this sense the challenges and opportunities for the physicist of today. In addition to the figure of Data Scientist, specialized purely in the analysis of large amounts of data, it is increasingly clear the need to also train figures able to develop the methods and techniques that are fundamental for such analysis - in this sense we named the program of Physics of the Data. Training in Physics, Mathematics and Computation is increasingly necessary to generate such innovation and development. The program will thus train a new generation of physicists, which we could define as "data physicists", equipped with tools that will allow them to face the challenges that the digital revolution has brought in our society .

Occupational opportunities
Graduates will have jobs opportunity in Italy and abroad in:
- academic institutions;
- research centers;
- internet companies, consulting companies;
- startups and high tech industries;
- public administrations.

  Teaching list

I Anno BIOLOGICAL DATASETS FOR COMPUTATIONAL PHYSICS SUBNUCLEAR PHYSICS [ DONATELLA LUCCHESI ] INFORMATION THEORY AND INFERENCE STRUCTURE OF MATTER [ LUCA SALASNICH ] RELATIVISTIC ASTROPHYSICS [ GIACOMO CIANI ] COSMOLOGY [ SABINO MATARRESE ] VISION AND COGNITIVE SERVICES NETWORK MODELLING [ MICHELE ZORZI ] MACHINE LEARNING [ PIETRO ZANUTTIGH ] THE PHYSICAL UNIVERSE [ SABINO MATARRESE ] STATISTICAL MECHANICS [ ENZO ORLANDINI ] STATISTICAL MECHANICS OF COMPLEX SYSTEMS [ AMOS MARITAN ] SOLID STATE PHYSICS [ FRANCESCO ANCILOTTO ] NUCLEAR PHYSICS [ SILVIA MONICA LENZI ] LABORATORY OF COMPUTATIONAL PHYSICS (MOD. B) [ MARCO BAIESI ] LABORATORY OF COMPUTATIONAL PHYSICS (MOD. A) [ MARCO ZANETTI ] ADVANCED STATISTICS FOR PHYSICS ANALYSIS MANAGEMENT AND ANALYSIS OF PHYSICS DATASET (MOD. B) [ JACOPO PAZZINI ] MANAGEMENT AND ANALYSIS OF PHYSICS DATASET (MOD. A) [ GIANMARIA COLLAZUOL ] THEORETICAL PHYSICS [ PIERPAOLO MASTROLIA ] THEORETICAL PHYSICS OF THE FUNDAMENTAL INTERACTIONS [ STEFANO RIGOLIN ] GENERAL RELATIVITY [ MARCO PELOSO ] MODELS OF THEORETICAL PHYSICS [ AMOS MARITAN ] FINAL EXAMINATION LABORATORY OF COMPUTATIONAL PHYSICS (C.I.) [ MARCO ZANETTI ] MANAGEMENT AND ANALYSIS OF PHYSICS DATASET (C.I) [ GIANMARIA COLLAZUOL ] II Anno QUANTITATIVE LIFE SCIENCE [ SAMIR SIMON SUWEIS ] QUANTUM INFORMATION AND COMPUTING [ SIMONE MONTANGERO ] COMPUTATIONAL ASTROPHYSICS [ MICHELA MAPELLI ] ASTRO-STATISTICS AND COSMOLOGY [ MICHELE LIGUORI ] GAME THEORY [ LEONARDO BADIA ] NETWORK SCIENCE [ TOMASO ERSEGHE ] DIGITAL SIGNAL PROCESSING NEURAL NETWORKS AND DEEP LEARNING [ ALBERTO TESTOLIN ] LIFE DATA EPIDEMIOLOGY [ LEONARDO BADIA ] STAGE [ MARCO ZANETTI ]

Entry requirements:

  • Bachelor’s degree or equivalent, with proven skills in Physics and Mathematics
  • English language: B2 level (CEFR) or equivalent