Digital Health Specialisation
Digitalisation in the healthcare system improves diagnoses and creates opportunities for personalised treatments. Learn to tap into people as sources of data and contribute to preventing diseases and assisting patients.
Our specialization in "Digital Health" offers a forward-looking education at the intersection of medicine and technology. In this specialization, you will learn to analyze large amounts of data produced by humans through modern technology and use it for advancements in healthcare. The increasingly widespread use of technology such as sensors generates a significant amount of data ("Big Data"). This calls for specialists who can process, analyze, and understand this data. Graduates of the BSc program "Applied Digital Life Sciences" with a focus on "Digital Health" are precisely such experts.
The thematic focuses of the mandatory modules include medical fundamentals, biomedical devices, clinical informatics, and data science. This interdisciplinary approach prepares you to tackle complex challenges in the digital health sector.
«The future of healthcare is digital. It is, however, often difficult to understand and safely use the vast amounts of health data available. The Applied Digital Life Sciences degree programme with the Digital Health specialisation offers an exciting perspective here.»
Peter Ohnemus, President & CEO, dacadoo AG, Zurich
You will learn...
- fundamental knowledge of human anatomy, physiology, and diseases
- principles of medical devices such as sensors and imaging
- analysis of patient and laboratory data
- concepts, systems, and applications of clinical data processing
- basics of clinical study planning and statistical analyses for epidemiology, genetics, etc.
- knowledge of typical biomarkers in medical data and learning methods for identifying new biomarkers
Examples of projects you could work on in the future
- You could apply deep learning methods to patient genomes to develop new therapeutic approaches in cancer research. You might collaborate with a team from ZHAW and a pharmaceutical company.
- You might record movements and numerous other parameters in the sleep lab of a large hospital. Therefore, you would analyze these data to assess health conditions and improve patient monitoring.
- You could use sensors to collect vital parameters from horses. Therefore, you would employe machine learning algorithms to determine the ovulation phase of mares from the data, allowing for precise predictions of foal births without the need for previous invasive examinations.
Career
Companies in health, biomedicine, biotechnology and pharmaceuticals are typical employers. Would you like to know what career path you could follow after graduation? An overview is provided on our careers page.
The compulsory modules within the specialisation are supplemented by elective modules, which provide you with the opportunity to develop further, either in specific topics within the specialisation or supplementary topics. This enables you to create an individual course profile according to your interests.
It is possible to combine certain elective modules into a minor. A minor corresponds to at least 12 ECTS credits, of which about half is completed in the form of a project paper.
This module table is valid since 12. September 2022
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Grundlagen
Data Science & Computation
Projekte & Labs
Digital Life Sciences Module
1. Semester, ECTS: 30
Analysis & Algebra
ECTS: 6
English
ECTS: 2
Gesellschaft, Kultur, Sprache
ECTS: 2
Daten und Information
ECTS: 4
Programmieren
ECTS: 4
Physical Computing in Life Sciences
ECTS: 4
Anorganische Chemie
ECTS: 4
Biologie & Technikgrundlagen
ECTS: 4
2. Semester, ECTS: 30
Systeme & Modelle der Physik
ECTS: 4
English
ECTS: 2
Gesellschaft, Kultur, Sprache
ECTS: 2
Statistik und Wahrscheinlichkeit
ECTS: 4
Numerische Grundlagen d. Data Science
ECTS: 4
Datenzentriertes Programmieren
ECTS: 2
Versuchsplanung & Auswertung Praktikum
ECTS: 4
Systeme der Biologie
ECTS: 4
Organische Chemie
ECTS: 4
3. Semester, ECTS: 30
Math. Modelle und Analyse
ECTS: 4
Datenbanken
ECTS: 4
Statistische Modellierung & Simulation
ECTS: 2
Maschinelles Lernen
ECTS: 4
Data Engineering
ECTS: 4
Life Sciences Datalab - Praktikum
ECTS: 8
Life Sciences Datalab - Methoden & Techniken
ECTS: 4
4. Semester, ECTS: 30
Data & Society
ECTS: 2
Modelling of Complex Systems
ECTS: 2
Neural Networks
ECTS: 4
OS and Infrastructure
ECTS: 4
Signal & Image Processing
ECTS: 4
Projektarbeit - Praktische Anwendung
ECTS: 6
Human Anatomy & Physiology
ECTS: 4
Biomedial Measurements and Imaging
ECTS: 2
Microbiology
ECTS: 2
Genomics
ECTS: 2
5. Semester, ECTS: 30
Economy & Entrepreneurship
ECTS: 4
Optimisation and High Performance Computing
ECTS: 4
Projectorient. Digital Storytelling & Visualisation
ECTS: 4
Individuelle Projektarbeit LS Applikation
ECTS: 8
Clinical Data Processing
ECTS: 4
Fluid Dynamics
ECTS: 2
Pathophysiology
ECTS: 2
Bioinformatics
ECTS: 2
Machine Learning in Diagnostic Imaging
ECTS: 2
Molecular Imaging
ECTS: 2
Image Processing for Remote Sensing
ECTS: 2
6. Semester, ECTS: 30
Ethics and Law
ECTS: 4
Bachelor Thesis
ECTS: 16
Digital Biomarkers
ECTS: 4
Biostatistics in Epidemiology and Genetics
ECTS: 4
Laboratory Informatics / LIMS
ECTS: 2
Bioinformatics 2
ECTS: 2
Integrated Omics
ECTS: 2