MSc of Science - Medical Informatics

You will learn to combine the latest insights in information technology with a focus on the healthcare industry. You will explore areas such as biomedical data analysis, AI tools and big data and their applications in healthcare.

The emphasis is on personalized medicine: internships and seminars with leading healthcare providers address practical applications in health data analysis, software development for hospitals and pharma firms, along with ethical and data security considerations.

You will learn to combine advanced informatics, machine learning and mathematical techniques with a focus on the role of AI in drug discovery. You will be prepared to take on leadership roles in the digital transformation of the industry.

Thanks to a mix of theoretical knowledge and hands-on internships with leading pharma companies, the curriculum offers a comprehensive skill set, including insights into laboratory automation, digital biomarkers and key aspects of drug discovery.

The detailed structure of the Medical Informatics and Pharma Informatics programme can be found here:

View programme structure as PDF

The core modules introduce topics essential for success in the field of medical informatics. These are not offered in standard computer science courses.

• Medical Data Science: Learn to work with medical data by applying statistical methods, building predictive models, using machine learning and exploring AI tools such as ChatGPT in real healthcare contexts.
• Digital Transformation in Healthcare: Understand how digital technologies are reshaping healthcare systems, from hospital operations to pharmaceutical development and patient care.

• Digitalization of Business Processes in Healthcare: Explore how clinical and business processes in healthcare can be improved using digital systems, automation and workflow technologies.
• Medical Software Development: Gain insights into how software is developed for medical use, including international regulations, quality standards and everyday development practices.

• Foundations: Build a strong scientific base in genetics, physiology and biopharmaceutics while gaining an overview of how new drugs are discovered and developed.
• Applied Mathematics and Informatics in Drug Discovery: Work with mathematical models, bioinformatics tools and machine learning to solve problems in pharmaceutical research and drug development.
• Mathematical and Computational Biology in Drug Discovery: Learn core methods in computational biology, bioinformatics, and mathematical and statistical modeling used in drug discovery.

You can choose elective modules from a range of medical/pharma informatics topics, business modules and other modules that consider the dynamic nature of the field, in which technologies and challenges are evolving rapidly.

For both Specializations
• Machine Learning in Medicine: Use machine learning techniques to analyze healthcare data and support clinical and research applications.
• Development of Medicines and Medical Devices: Explore regulatory, safety and ethical aspects involved in drug development and clinical research.
• Quantum Computing: Get an introduction to how quantum computing principles can be applied in medicine and healthcare.
• Digital Biomarkers: Discover how digital indicators help identify particular diseases or physiological states of an organism, advancing medical diagnosis and monitoring.


Specialization in Medical Informatics
• Clinical Decision Support Systems: Design intelligent systems that help healthcare professionals make better decisions with real-time insights and patient-specific recommendations.
• Medicine and Informatics: Explore how immersive and data-driven technologies are transforming diagnostics, treatment and patient experience.
• HMI and Bias Mitigation: Learn to tackle bias in machine learning applications.
• Applied Computational Intelligence: Work with computational models and simulations to solve real-world medical and pharmaceutical problems using AI.
• Cyber Security in Health Care: Examine the risks and strategies for protecting medical data and connected devices from cyber threats.
• Medical Informatics Internship


Specialization in Pharma Informatics
• Business Intelligence: Learn how to support business decisions with facts by looking at different kinds of decisions, data and the tools required to distil information out of data.
• Cloud Computing: Gain practical skills in cloud technologies and understand how they support digital infrastructure in healthcare and pharma.
• Biomarkers: Understand key biomarker classes, their discovery, and their application in clinical diagnostics and research.
• Innovative Trends in Pharma Informatics: Take part in seminar-style sessions on emerging technologies and topics shaping the future of the pharma industry.
• Laboratory Automation in the Pharma Industry: Discover the role of automation in pharma labs, with foundations in cell biology, analytics and pharmacology.
• Artificial Intelligence in Drug Discovery: Apply AI methods and algorithms to accelerate and improve the drug discovery process.
• Pharmacokinetics and Dynamics: Model how drugs interact with the human body using computational tools in pharmacokinetics and pharmacodynamics.
• Pharma Internship

• Data Science: Explore AI and machine learning techniques, including neural networks and how they can be applied to medical data.
• User-Centered Design and Design Thinking: Learn to design effective, human-centered digital health solutions using design thinking principles.
• IT Governance, Risk and Compliance: Understand how organizations manage risk, compliance and digital strategy through global standards and frameworks.
• Knowledge Processing and Decision Making: Explore how machines acquire and use knowledge to support human decisions and improve system intelligence.
• Healthcare Entrepreneurship: Develop the mindset and tools to build innovative healthcare startups or ventures.

Specialization electives from Pharma Informatics can be taken as general electives for Medical Informatics and vice versa.

The Master's thesis is industry oriented and comprises 30 ECTS credits. Cooperation with external partners allows you to get industry experience during your thesis. You work on challenging, application-oriented informatics projects and you will be supervised by a lecturer from the Master's programme.

The diagram below shows how the programme is structured. After the core modules in your first semester you are free to choose from a range of electives. The programme concludes with your thesis.

Platzhalter Bild

The master’s programme begins in the autumn semester (calendar week 38).

According to the fee regulations of the University of Applied Sciences Northwestern Switzerland FHNW, the following semester and registration fees are charged. Further details can be found in the FHNW fee regulations, valid from the 2025/26 academic year.

Tuition fees per semester:

• CHF 750
• Swiss citizens
• Students whose legal residence is in Switzerland at the beginning of their studies
• Students who can provide proof that their parents had legal residence in Switzerland at the beginning of the studies
• Adult refugees and stateless persons with legal residence in Switzerland
• CHF 1 000
• For students whose legal residence at the beginning of their studies is in an EU/EFTA country
• CHF 5 000
• For students whose legal residence at the beginning of their studies is in neither Switzerland nor an EU/EFTA country

An additional fee of CHF 100 per semester is charged for materials and licenses.

The full semester fees are due unless withdrawal is submitted to the FHNW within one week after the semester begins.

Study and examination regulations German (PDF)

Flyer MSc Medical Informatics Englisch (PDF)