Society, health, environment, and nutrition – these are the areas we focus on in the life sciences. As global challenges grow, so do the hopes and expectations for innovation within the life sciences. To meet these demands, life scientists must be agile, forward-thinking, and creative – and this is achievable through expanded skills in artificial intelligence and computational science.

From early detection of strokes through digital twins and computer-aided drug development to ecosystem modelling for nature conservation measures – such advancements are driven by computational life sciences.

In our Master’s programme, you’ll broaden your skills and build a bridge to the world of data. You can apply what you’ve learned immediately in practical projects, becoming part of a research group and collaborating with our industry partners. 

This hands-on experience provides you with the ideal preparation for diverse career opportunities.

Deepen your knowledge in one of these 5 tracks:

Computational Health

Use data- and model-based methods for addressing medical challenges. You will leverage machine learning on diverse medical data to uncover causal relationships. In doing so, you’ll employ technologies such as wearables and biosensors, discover digital biomarkers, and create tangible digital health solutions.

Video portrait graduate: Shannon Vlahakis - From Health Scientist to Data Scientist at the Centre for Computational Health

Video portrait graduate: Sofia Rey - From Neuroscientist to Healthcare Management Consultant at Swisscom

Bioinformatics

Work at the intersection of biology, medicine, and computer science. In this track, you’ll engage with the modelling of molecular biological processes, multi-omics approaches for biomarker discovery, the study of genomic evolution and adaptive changes, as well as the representation and integration of biomedical data.

Video portrait graduate: Moritz Kaufmann - From biotechnologist to PhD in Data Science

Digital Environment & Sustainability

Engage in sensor- and AI-based monitoring and modelling of natural systems and their interaction with humans. This includes questions related to smart farming and sustainability in a broader context, for example, concerning social and economic issues.

Interview graduate: Patricia Kreyer - What could a vegan world look like?

Digital Labs & Production

Connect people, spaces, and processes. In this track, you will focus on methodological and technological expertise in the digitalisation and virtualisation of labs, processes, and production facilities.

Video portrait graduate: Christopher Keim - From Biotechnologist to Head of Process Automation at Food Brewer

Interview graduate: David de la Gala - From Beer Brewer in Bavaria to Technical Project Manager at Unilever (Interview in German)

AI & Robotics in Life Sciences

Create new solutions based on a fundamental understanding of humans and machines as a unified learning system. In this track, you will focus on the application of deep learning, natural language processing (NLP), and intelligent robotics in human interaction.

The opportunities for graduates in this rapidly developing field of research and business are practically endless. Many find employment during their studies. They work as data analysts, data scientists, application developers or researchers in a wide range of industries, including pharmaceuticals, biotechnology, agro-food, environment and medicine.

Suitable students have the opportunity to join our Data Science PhD programme, which is conducted in partnership with various Swiss universities.

• We offer a customisable Master’s programme which you can complete in 3, 4, 5, 6 or 7 semesters.
• The programme offers an attractive mix of modules from research, science, practice and business.
• You will have the opportunity to grow both as a professional and as a person, and to evolve into a sought-after specialist with leadership skills.
• We offer exciting research projects for your Master's thesis.
• You will be able to join a research group, where you can practice skills such as teamwork, initiative and critical thinking.
• You will benefit from small class sizes in the advanced modules, which offer interactive learning activities that will allow you to take charge.

• Processing and analysing data of various sizes and levels of complexity.
• Conceptual and technical skills to combine your expertise in a life sciences discipline with the potential of computational methods.
• Computational modelling and simulation of processes.
• Statistical modelling with machine learning and neural networks.
• Programming using modern scripting languages such as Python and R and you will understand the basic concepts of software and computer architectures.
• Analysis and solving  of complex problems that combine scientific, social and entrepreneurial thinking.
• Planning, implementation, evaluation and presentation of major research and development projects.

^{Orange: Specialisation Modules / Green: Cluster Modules - you choose at least 9 ECTS / Blue: Core Competences - you choose at least 12 ECTS
Solid colours: mandatory modules / Light colorus: elective modules}

The picture above shows the general structure of a full-time Master's programme. Students design their own study paths and choose their own focal points.

Together with your supervisor, you design your own individual study plan from the range of compulsory and elective modules. The selected modules are recorded in your individual study agreement (planning).

In addition, elective modules from the specialisations of Pharmaceutical Biotechnology, Chemistry for the Life Sciences or Food and Beverage Innovation can be taken.