The Health Informatics master's degree, a joint programme between Vita-Salute San Raffaele University (UniSR) and Politecnico di Milano, was designed to address a specific, measurable problem. According to Politecnico di Milano's Digital Health Observatory, 61% of medical specialists already use artificial intelligence tools in clinical practice, but only 2% have the advanced digital skills to manage them well. At the same time, demand for healthcare data analysts in Italy has grown by more than 20% a year since 2022.
Taught entirely in English, the programme was designed to close the gap between those who generate clinical data and those who know how to interpret it. «It's the first computer science degree in Italy actually born inside a hospital, thanks to the partnership between UniSR, San Raffaele Hospital and Politecnico di Milano,» notes Prof. Antonio Esposito, the programme's coordinator.
UniSR's translational biomedical research, carried out in partnership with IRCCS San Raffaele Hospital, one of Italy's leading scientific research and treatment centres, is paired with Politecnico di Milano's technological expertise in computer science and engineering. For students, this translates into two concrete things: courses are taught by faculty from both universities, and theses can grow out of a real research project.
The goal is to train professionals capable of working on precision medicine and treatment personalisation, a different task from managing a hospital's information systems. In the United States, hybrid training between clinical practice and engineering has a long history: Harvard Medical School and MIT have collaborated since 1970. In Italy, UniSR and Politecnico di Milano's Health Informatics programme is the first to offer a joint interuniversity degree between a medical university with its own IRCCS and a polytechnic, with the chance to work in laboratories at both institutions.
The programme lasts two years, is taught entirely in English and awards a joint degree between the two universities: not two separate diplomas, but a single title that UniSR and Politecnico di Milano validate and recognise together. Half the teaching staff come from UniSR, the other half are specialists from Politecnico di Milano.
The programme opens doors to healthcare IT companies, hospitals, and to startups and scale-ups whose core business is AI applied to medicine. From the first semester, those who enrol follow the track that best complements their background. Students arriving from a technical computer science background focus on Biology, Genetics, Anatomy and Physiology, while those with a medical or biological background focus on Software Systems Design and Operations. This way, every student builds the knowledge that completes their training and arrives prepared for the shared part of the programme, where the two skill sets have to work together.
This dual entry point addresses a real problem that programme faculty have observed on the job market. Practitioners with a double specialisation in computer science and medicine are still rare, and tend to be lopsided toward one discipline or the other: too technical to talk to clinicians, or too clinical to work efficiently with data. The two-track structure exists to correct this imbalance from the start, before graduates enter the job market.
Lessons alternate with hands-on lab work at UniSR and Politecnico di Milano. AI-HUB, the artificial intelligence centre run by UniSR and San Raffaele Hospital in partnership with Microsoft, gives students access to real clinical big data, not simulated cases, to build machine learning and deep learning models in oncology, cardiovascular disease and neurology. Theses, too, can grow out of a real research project in either university's labs.
What sets the programme apart from a data science master's applied to healthcare is its ethics component, built into the curriculum from year one. Faculty who teach epidemiology and clinical research in the programme point out that the questions raised by artificial intelligence in diagnostics, prognosis and treatment choices are, first and foremost, questions of clinical responsibility.
A concrete example comes from research on bias in medical AI: in a study by Gaube and colleagues, a group of general practitioners assessed clinical cases with the support of an AI system. When the system suggested a wrong diagnosis, many doctors abandoned their own correct initial assessment to align with the algorithm's suggestion, a pattern known as automation bias. Health Informatics graduates who understand this mechanism don't stop at building the model: they know how to design the interface and the protocols that reduce the risk of doctors relying on the algorithm more than they should.
With the EU AI Act now in force, healthcare organisations that adopt artificial intelligence systems must ensure traceability, human oversight and risk management across the tool's entire lifecycle. The programme prepares students for this too, teaching them to design platforms that meet these requirements from the development stage onward.
Students are often approached by companies before they even finish the programme. A dedicated career day, organised by UniSR and Politecnico di Milano, connected second-year master's students with technology and healthcare organisations to talk about internships and early-stage interviews.
The programme prepares graduates for roles such as Data Analyst or IT Analyst, with the possibility of growing into positions like Chief Artificial Intelligence Officer or Chief Health Information Officer at hospitals, research institutions and companies in the sector. These are new roles, in high demand on the job market because so few candidates have the skills to fill them. The degree also grants access to the State Exam for registration with the Register of Information Engineers, a qualification recognised outside healthcare too.
The programme launched only a few years ago, so a full picture of graduate employment outcomes is still a few years away. But the market these graduates are entering is already growing fast: according to a Mordor Intelligence estimate, the global market for artificial intelligence in medicine was worth about USD 31 billion in 2025 and could exceed USD 185 billion by 2030.
The admissions calendar set by UniSR and Politecnico di Milano reflects this growth phase: several selection rounds take place across the same academic year, so those who discover the programme after the first deadline still have a real chance to apply. Applicants whose degree doesn't exactly match the requirements can also apply: an admissions committee evaluates prior credits case by case.