Master of Science in Life Sciences - Applied Computational Life Sciences
Programming, Algorithms, Data-Structures, Mathematical Modelling, Machine Learning, Pattern Recognition, Data Bases, Data Architecture Systems, Handling and Visualising Data, Neural Networks and Deep Learning are the relevant Keywords. Those who master these contents have key qualifications for the future. Become a data scientist and simulation expert!
The digital revolution is giving rise to profound changes in both science and business. Expertise in dealing with digital tools and large volumes of data is becoming an essential skill for specialists. In this Master's programme, you will acquire these exact skills and combine them with your subject-specific experience and your knowledge from previous studies.
The job market is calling for specialists with specific skills in data management, modeling and simulation. On the one hand, you will have excellent job prospects in the various areas of the life sciences. On the other hand, you will be a sought-after specialist at universities, authorities and in national and international organisations.
"I studied Health Sciences and Technology at the ETH, specialising in neuroscience. Since the topic of data science has become increasingly important in recent years, I also completed a Master's degree in Applied Computational Life Sciences at the ZHAW. This enabled me to expand my expertise with digital skills such as programming, neural networks and machine learning. In my current job as team leader responsible for the clinical information system (HIS) at Hirslanden, I use this mix of skills on a daily basis."
Sofia Rey, Team Leader Clinical Information System, Hirslanden
You are fascinated by topics such as: Artificial Intelligence and Predictive Analytics, Biomedical Simulation, Citizen Science Technologies, Climat Modelling, Complex Systems, Computational Genomics, Data Iintegration and Semantic Web Technologies, Digital Health, Forecasting & Decision Making, Geoinformatics, Health Technologies, Lab Information and Management Systems LIMS, Personalized Medicine, Process Optimization in Food Technology, Smart Environmental Systems, Smart Farming.
You have a Bachelor's degree in: Agronomy, Bioanalytics and Cell Biology, Biology / Biotechnology, Chemistry, Energy and Environmental Technology, Information Technology, Engineering, Food Science and Management, Food Technology, Medical Technology, Pharmaceutical Technology, System Technology, Environment and Natural Resources, Environmental Technology, Forest Sciences or similar (admission with other degrees may be granted at the programme directors' discretion).
This specialisation in Applied Computational Life Sciences lays the foundation for a career in a rapidly developing field of research and business. The programme provides essential knowledge in a field where science meets business, and opens up career paths in international companies, agile start-ups and research institutions.
As a graduate of this programme, you will find a job that shapes the future.
Suitable students have the opportunity to be accepted onto our Data Science PhD programme run in collaboration with other 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.
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).
During your studies, you will expand your personal skillset not only in terms of technical expertise and methodology, but also in terms of self-management. The practice-oriented research focus of your Master's thesis will foster your ability to innovate, change perspectives, and combine entrepreneurial with scientific thinking.
The work in your research group will not only help you develop your creativity, initiative and critical thinking abilities, but also your leadership and teamwork skills. We promote inductive, inquiry-based learning in small classes with interactive learning activities such as group work and presentations.