Scientific and Data-Intensive Computing
The Master’s Degree program in Scientific and Data-Intensive Computing is designed to prepare professionals capable of tackling the crucial challenges of the digital society in areas such as computational science and engineering, digital twin, high-performance computing, and data-intensive computing.
These figures, by integrating knowledge of classical modelling with knowledge of high-performance computing and modern methods of data management and analysis, can find employment in a variety of fields, including research, development and design centres, both public and private, in industrial and scientific technology, computing laboratories, companies providing services for the processing of large volumes of data, financial, banking or insurance institutions, service companies and independent consulting firms.
The program provides students with a solid methodological preparation in three main areas: data analysis and machine learning, mathematical and computational modeling, and computer science, with particular attention to high-performance and distributed computing.
The student will deepen his skills in some foundational aspects depending on the chosen curriculum, and can then complement his training with courses in applied areas of the physical and natural sciences and engineering. The student will acquire not only theoretical knowledge, but also the ability to apply it to the solution of practical problems through individual exercises and group projects. The training will be complemented by seminar courses and by an internship and thesis activity that can be carried out in companies and research institutions.
The program is international, taught in English, and organized by the University of Trieste jointly with the University of Udine, in collaboration with SISSA, ICTP, Area Science Park, and other research institutions in the Trieste area and the Friuli Venezia Giulia region.
Call for application is open.
DeadlineAugust 25 (13.00 CEST)
The master program prepares professionals capable of facing crucial challenges of the digital society in the areas of computational science and engineering, digital twins, high-performance computing and data intensive computing.
Computational Modeling and Digital Twins
The curriculum trains graduates proficient in modern numerical simulation techniques, with strong skills in modern techniques that integrate data and machine learning approaches.
High Performance Computing and Data Engineering
The curriculum trains graduates who are experts in modern techniques of high-performance computing and the management of big data.
The curriculum trains graduates who are experts in quantum computing and its applications.