Artificial Intelligence is fundamentally transforming healthcare. The Master’s degree programme Applied AI in Healthcare enables you to actively shape this transformation at the intersection of technology, medicine, and society. Throughout the programme, you will gain in-depth expertise in Artificial Intelligence, Data Science, and Machine Learning, and learn how to apply these technologies effectively in clinical environments. The focus lies not only on developing AI models, but above all on integrating them into real healthcare processes and systems. The programme combines technological expertise with medical practice and prepares you for a key role in the digital transformation of healthcare. Become part of a new generation of experts who make Artificial Intelligence impactful where it matters most – in healthcare.
| Study mode: | part-time with on-site, online and blended-learning components |
|---|---|
| Degree awarded: | Master of Science (Continuing Education) – MSc (CE) |
| Length of study: | 4 semesters (120 ECTS) |
| Study places per year: | Approx. 20–25 students per cohort |
| Locations: | Salzburg University of Applied Sciences (Campus Urstein) and Paracelsus Medizinische Universität (Salzburg) |
| Language of instruction: | English |
| Study format: | Blended learning (online + on-site) |
| Class schedule: | dates see below |
| Tuition fee: | € 15,000 |
Why Study Applied AI in Healthcare?
- Unique Collaboration: Salzburg University of Applied Sciences, Paracelsus Medical University (PMU), and Salzburg University Hospital
- Practice-Oriented: Work on real clinical challenges and datasets
- Interdisciplinary Approach: Combining IT, medicine, data analytics, and management
- Focus on Implementation: From concept to integration into clinical workflows
- Future Skills: AI, Data Science, ethics, and regulatory requirements in healthcare
During the programme, you will explore the technological, clinical, and societal dimensions of AI in healthcare in depth.
Key topics include:
- Artificial Intelligence and Machine Learning in clinical contexts
- Data analytics and data management in healthcare
- Clinical Decision Support and medical image analysis
- Integration of AI into clinical processes and systems
- Explainable AI, quality assurance, and patient safety
- Legal and ethical frameworks (e.g. EU AI Act, European Health Data Space)
Through project-based learning and real-world use cases, you will develop solutions that can be directly applied in practice.
As with other IT Master’s programmes at Salzburg University of Applied Sciences, the focus is on combining technical expertise, interdisciplinary collaboration, and practi-cal implementation.
Programme Structure & Teaching Format
The programme is designed for working professionals and spans four semesters.
- Blended Learning: Combination of online teaching and compact on-site sessions
- 1st and 2nd semester:
Weekly on-campus day (Thursday from 1.30 p.m.) + 1 - 2 Saturdays per month
Block week (16–20 November 2026; optionally 18–22 January 2027) - 3rd and 4th semester
Compact on-site phases
- 1st and 2nd semester:
- Project-Based Learning: Development of projects in cooperation with clinics and partners
- Interdisciplinary Teams: Collaboration between students from different professional backgrounds
- Expert Input: Guest lectures and practical insights from academia and industry
At the core of the programme is the continuous work on real-world challenges – from the initial idea to practical implementation.
Career Opportunities
As a graduate, you will possess a highly sought-after skill set at the intersection of AI and healthcare.
Possible Career Paths:
- Clinical Data Scientist
- AI Health Solutions Developer
- Digital Health / AI Project Manager
- Specialist for Clinical Decision Support Systems
- Interface role between IT, clinical practice, law and quality management
- Public Health Data Expert
- Transformation management in healthcare
This programme prepares you to develop and implement data-driven innovations in healthcare.
Applications for the 2026/27 academic year are open now until 30 August 2026.