Master's program Applied AI in Healthcare
Target groups & Eligibility requirements

This programme is designed especially for healthcare professionals and graduates who want to understand and apply artificial intelligence in medical and healthcare settings without requiring deep prior technical expertise. It is particularly suited to individuals from medicine, nursing, health sciences, biomedical sciences, healthcare management, public health, or related fields who wish to build practical AI competencies and contribute to digital transformation in healthcare.

The curriculum introduces key concepts in Artificial Intelligence, Data Science, and Machine Learning in an applied and healthcare-oriented way. Rather than assuming an advanced technical background, the programme supports students in developing the necessary digital, analytical, and methodological skills step by step, with a strong focus on real clinical contexts, responsible implementation, and interdisciplinary collaboration.

Graduates will be prepared for interface roles between healthcare practice, IT, research, and management, as well as positions such as Digital Health or AI Project Manager, Clinical Data Scientist, Specialist for Clinical Decision Support Systems, or Innovation and Transformation Manager in healthcare.

By combining healthcare expertise with applied AI knowledge, the programme enables graduates to evaluate, communicate, and implement data-driven innovations that can improve processes, support healthcare professionals, and contribute to better patient care.

Applicants to the Continuing Education Master’s Programme Applied AI in Healthcare must provide the following evidence as part of their online application:

Required Qualifications

• Completed subject-relevant degree at Bachelor’s level or equivalent, comprising at least 180 ECTS credits
• At least two years of relevant professional experience in healthcare, health-related organisations or related sectors
• Demonstrated interest in Artificial Intelligence / Machine Learning and its responsible application in healthcare
• Proof of English language proficiency at B2 level according to the CEFR

Subject-Relevant Backgrounds

Relevant academic or professional backgrounds may include:

• Medicine, healthcare, nursing, public health or health sciences
• Allied health professions
• Natural sciences with a healthcare focus
• Psychology, psychotherapy or social work in a healthcare context
• Healthcare management, health economics or hospital management
• Law with a medical, health, data protection or AI-regulatory focus
• Computer science, medical informatics, biomedical engineering or health informatics

Equivalent healthcare qualifications, including qualifications at EQF/NQF level 6, may be recognised following individual review.

Relevant Professional Experience

Professional experience may come from:

• hospitals, clinics, laboratories, nursing homes or rehabilitation facilities
• outpatient care, primary care, emergency services, therapy practices or public health
• healthcare-related private-sector organisations, such as MedTech, pharma, insurance, healthcare start-ups, consulting, quality management or digitalisation projects

Experience with clinical processes, digital systems, structured data, quality indicators, decision support, reporting, process improvement or innovation projects is particularly relevant.

Interest in AI and Digital Health

Advanced technical expertise is not required. Applicants should, however, demonstrate a clear interest in understanding AI/ML methods and applying them responsibly to healthcare-related questions.

Suitable evidence may include:

• experience with digital or data-driven healthcare systems
• participation in AI, digital health, data quality or process improvement projects
• continuing education, workshops, webinars or self-directed learning
• a short healthcare-related AI use case from the applicant’s own professional field
• participation in relevant conferences, working groups or innovation initiatives

English Language Proficiency

Applicants must provide proof of English language proficiency at B2 level or equivalent. Recognised evidence may include:

• standardised language tests such as TOEFL, IELTS, Cambridge English Qualifications or PTE Academic
• school-leaving certificates with English as an examination subject
• successful completion of an English-language Bachelor’s degree
• exemption for applicants whose first language is English

Selection Procedure

The selection procedure consists of:

• a motivation letter of two to three pages explaining the applicant’s professional relevance and motivation
• a structured application interview of approximately 20 minutes with representatives of Paracelsus Medical University and Salzburg University of Applied Sciences

Admission is granted after successful review of the submitted documents and completion of the selection procedure.