Enrollment Process

The Didactic Regulations require that, to get access the master’s degree in Information Engineering for Digital Medicine, prospect students must meet specific requirements related to:

• Curricular disciplines (that is, students must have gained a certain number of credits in specific subject areas).
• Knowledge of the English language.
• Background/personal knowledge.

For further details, please see the following documents published in the regulation section:

• Didactic regulation of the degree's program (particularly, with reference to Art. 3).
• Procedures for verifying admission requirements for the master’s degree program.

The Admission Test

Background/personal knowledge is assessed via an admission test. The specific dates for the test are determined on a yearly basis and are available from the website of the Department in Information and Electrical Engineering and Applied Mathematics.

The minimum score to pass the test is 60 points. As specified in the regulations, the score points – maximum score is 100 – are partitioned as follows:

• Up to 20 points for the titles related to the prior Academic career.
• Up to 80 points for the admission test.

Concerning the admission test, which has the goal to assess the level of preparation of prospective students on the curricular disciplines, it consists of 5 exercises, each related to topics included in the Syllabus at the bottom of this page.

Exemptions from the test are granted only in specific cases: please refer again to the document Procedures for verifying admission requirements for the Master’s Degree Programme.

The upcoming dates for the assessment test are announced:

• Friday, July 18, 2025
• Friday, September 26, 2025
• Friday, December 12, 2025
• Friday, February 20, 2026

For information on how to participate in each session, please contact: carrierestudenti.diem@unisa.it no later than 10 days before the scheduled date.

Admission Test Syllabus

Basic disciplines

• MATHEMATICS – Functions and differential calculus of one or more real variables. Vectors in the plane and in Euclidean space; vector spaces. Linear systems. Integral calculus. Complex numbers. Matrix algebra. Eigenvalues and eigenvectors. Complex analysis.
• PHYSICS – Kinematics. Dynamics of a particle and systems of particles. Work and energy. Rigid body dynamics. Gravity. Electric fields. Electric current and circuits. Magnetic fields. Electromagnetic induction.

Characterizing and Engineering disciplines

• AUTOMATIC CONTROL – Analysis of linear time-invariant dynamic systems in the complex and frequency domains. Classical feedback control of linear systems. Analysis of discrete-time linear systems in the complex domain.
• CIRCUITS – Methods for analyzing time-invariant linear electric circuits in the time and frequency domains. Analysis of resistive and dynamic circuits under steady-state conditions. Analysis of basic filters. Analysis and synthesis of combinational and sequential logic circuits. Hardware description languages (e.g., VHDL).
• TELECOMMUNICATIONS – Probability spaces and random variables. Analysis of continuous-time and discrete-time signals and systems, both deterministic and random, in the time and frequency domains. Methods for numerical signal processing.
• PROGRAMMING AND SOFTWARE – Fundamentals of structured programming. Basic data structures: arrays, matrices, records. Key algorithms for sorting and searching. Core data structures: stacks, queues, lists, binary search trees, hash tables. Techniques for analyzing and designing recursive algorithms. Object-oriented programming paradigm. Classes, instances, methods. Abstract data types, encapsulation, visibility rules. Interface and implementation inheritance. Polymorphism, substitution principle, dynamic dispatch. Exception handling. Fundamentals of concurrent programming. Time and space complexity of algorithms.
• ARCHITECTURES AND NETWORKS – Analysis and synthesis of combinational and sequential logic circuits. Common sequential and combinational machines. Principles of organization and low-level programming of a computer. Architecture and sizing of computer components: CPU, memory, I/O devices. Architectures and models of computer networks: layered model, packet-switching networks, ISO/OSI. Internet and LAN architecture. TCP/IP protocols.
• DATABASES AND OPERATING SYSTEMS – Relational model: tables and constraints. Database architecture and models. Database design: conceptual, logical, and physical levels. Architecture and features of transactional systems. Structure of an operating system. Main characteristics of modern OSs. Process/thread scheduling and synchronization, memory management, file system management. Common OS commands.

Additional Information