Dig­i­tal Life Sci­ences, FHNW School of Life Sciences

Digitalisation plays a central role in the BSc in Life Sciences: from the first semesters you will work in labs and on projects using digital tools, data systems and automated processes. You will learn how modern technologies are changing biological, chemical and environmental science, and how to use data to develop new solutions.

In modules such as Bioinformatics & Biological Databases, Introduction to Programming, Databases and Data Modelling and Methods of Artificial Intelligence, you will build up specific digital skills. In most fields of study you can also do a cross-disciplinary qualification in digitalisation: in-depth preparation for data-driven and technology-supported methods.

This will equip you to think experimentally, digitally and across disciplines - an increasingly sought-after capability in life sciences research and industry.

In the MSc in Life Sciences you will learn how digitalisation is becoming a key skill in the field: you will learn to understand and structure data and convert it into value-adding processes – from experimental and process data to automation, visualisation and data-driven decision-making. This is your path into an industry in which biological, chemical and pharmaceutical problems are increasingly being solved with digital tools.

For those who want to go one step further, the Data Science specialisation offers in-depth training in modern data science methods: you will learn programming, algorithms, database design and deep learning techniques. Elective modules allow you to focus on genomics, proteomics or laboratory automation, for example, while building key skills in data visualisation, multivariate data modelling and data handling ethics.

The MSc in Medical Informatics applies digital technologies and artificial intelligence to healthcare, focusing on the latest information technologies for the medical and pharmaceutical industries. Students acquire IT knowledge and methods, and deepen their skills in biomedical data analysis, the application of artificial intelligence, visualisation technologies, big data handling and the related economic implications.