Master of Science in Life Sciences - Applied Computational Life Sciences
There is a growing need for experts who have specific knowledge in a scientific discipline combined with skills in data science, modelling and computation.
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!
Best prospects for a successful future!
Master of Science in Applied Computational Life Sciences
Science and business are undergoing profound changes as a result of the developments of the digital revolution. Expertise in working with digital tools and large quantities of data are key supplementary skills for subject specialists. In this Master’s programme, you will acquire these supplementary skills and combine them with the subject-specific experience and knowledge gained in your Bachelor’s degree.
Do you have a Bachelor’s degree in one of the following fields or in a related field?
- Bioanalytics and Cell Biology
- Energy and Environmental Technology
- Environment and Natural Resources
- Environmental Technology
- Food Science and Management
- Food Technology
- Forest Sciences
- Information Technology
- Medical Technology
- Pharmaceutical Technology
- System Technology
Are you fascinated by the potential of digital technology? Then come and master up your degree by becoming a data scientist and simulation expert!
Interested persons with other backgrounds should contact the Program Advisor directly Dr. Manuel Gil
Flexible Study Agreement
Before your studies begin, you decide on your personal educational goals, define the topic of your Master’s thesis and create your individual study plan together with your supervisor from the selection of available modules. Your personal study programme is based on your educational background, your interests and your objectives. You will be able to profit from close interaction with your supervisor both at the beginning and throughout your studies. The Study Agreement is a learning tool that defines the balance between independent learning, contact lessons and e-learning. It enables you to create your own contemporary learning context that incorporates a high degree of flexibility.
Studying Applied Computational Life Sciences
Structure at semester start in autumn:
Your Field of Interest
Are you interested in any of the following fields?
- Artificial Intelligence and Predictive Analytics
- Biomedical Simulation
- Citizen Science Technologies
- Climate Modelling
- Complex Systems
- Computational Genomics
- Data Integration and Semantic Web Technologies
- Digital Health
- Forecasting & Decision Making
- Health Technologies
- Lab Information and Management Systems LIMS
- Process Optimization in Food Technology
- Smart Environmental Systems
- Smart Farming
You can choose your thesis topic and your advisor based on your field of interest. You will be placed in one of our specialisation tracks, which will prepare fully for your Master’s thesis in your field of interest.
Hand-On Master's Thesis
Your new Skills
- 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 in your Bachelor’s discipline
- programming using modern scripting languages such as Python and R, you should 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
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.
The Master of Science in Life Sciences is a cooperative venture run by the ZHAW together with three other Swiss Universities of Applied Sciences:
- The Berne University of Applied Sciences BFH
- University of Applied Sciences and Arts Northwestern Switzerland FHNW
- University of Applied Sciences and Arts Western Switzerland HES-SO
As part of the cooperation modules, you will benefit from the expertise of all four partners, create an extensive network, and participate in interdisciplinary exchanges.
Brochure Master's programme Applied Computational Sciences
At a glance
Degree / Title: Master of Science (MSc) ZFH in Life Sciences with specialisation in Applied Computational Life Sciences
Duration: Full-time 3 semesters, part-time possible (recommendation 4-7 semesters)
Start of studies: twice a year in February (spring semester) and September (autumn semester). If you start in February we recommend to study in part-time due to the structure of the specialisation modules.
Cooperation: Some modules take place jointly with the universities of applied sciences BFH, FHNW and HES-SO.
Workload: 90 credits (ECTS), one credit point corresponds to 25 – 30 hours of work
Teaching locations: Wädenswil, Olten or Berne. Block weeks can also be held directly at partner universities.
Study fees: CHF 720.00 (EUR 650 / USD 730) per semester + additional study-related expenses ...»
Admission requirements / acceptance: University of Applied Sciences Bachelor's degree ...»
Registration deadlines: 30th April and 31th October ...»
Missed the deadline? Please contact the Registrar's Office Master Life Sciences, firstname.lastname@example.org
Studies – Structure and Content
Your studies include different areas of competence plus a Master's thesis, with a total of 90 credits (ETCS).
Before commencing your studies, you will develop, together with the specialisation team and your supervisor, your personal training goals, define the topic for your Master's thesis and create your individual curriculum from the modules on offer.
The selected modules are recorded in your Individual Study Agreement (ISA).
Modules, topics and tracks
The study consists of different categories of modules::
1. Modules in the specialisation (Specialisation Skills):
- Core modules: Competencies in the handling of digital tools, including dealing with data, modeling and simulation
- Specialisation Track modules: Preparation for the Master Thesis in a specific field of application
- Master's thesis: The core of your studies
2. Modules in combination with the MSc Life Sciences:
- Core Competencies: Generic modules to deepen topics that are relevant to your studies
- Cluster-specific modules: Interfaces between the technical and scientific core area and the economic and social environment
Core Modules - 20 credits
This module group consists of the following 4 modules: Programming, Algorithms and Data Structures, Mathematical Modeling, Databases and Data Architecture Systems, Machine Learning and Data Analytics
Classes are usually held on Mondays and Tuesdays in Wädenswil.
Specialisation Track Modules - 10 credits
During two modules, you can deepen the thematic scope of your master's thesis. Classes are usually held on Monday and Tuesday in Wädenswil.
Master's thesis - 30 credits
On the basis of research you have carried out, you answer a specific question in this field and work out concrete solutions that are relevant for research, industry and society, often in co-operation with national and international partners. Through the thesis you not only demonstrate your knowledge and skills, but also expand the state of research in your specific field of scientific expertise.
Core Competencies – minimum 15 credits
These modules provide you with work-oriented skills. With these core competencies you acquire knowledge in the following areas: «Management, Business and Society» as well as «Handling and Understanding Data». Each module lasts half a semester – 2/3 of the lessons are held centrally in Olten and 1/3 consists of decentralised teaching (accompanied exercises, case studies etc.) directly in Wädenswil. You choose at least five from seven modules, of which all «Handling and Understanding Data»-modules are mandatory for the ACLS specialisation.
Cluster-specific modules – minimum 9 credits
Cluster-specific modules complement the specialisation modules. The specialisation Applied Computational Life Sciences is part of the group BECS (Biomedical Engineering and Computational Science). You choose modules out of the group BECS, two of which are mandatory modules. In addition you also can choose elective modules out of all other clusters (see list by the module descriptions).
The Master's programme in Life Sciences takes 3 full-time semesters and comprises 90 credits (ECTS). This corresponds to a workload of approximately 2,700 hours. This intensive workload requires good planning and organisation.
Part-time study opens up numerous ways to achieve the objectives of the programme - adapted to your personal circumstances and needs. We recommend that students do not engage in any additional professional activities that exceed a maximum workload of 50% of a full-time position. You should consult your specialisation team individually about this matter. For administrative questions, please contact the registrar's office.
How you structure your part-time studies should be discussed and determined before commencement thereof when creating your Individual Study Agreement (ISA).
Researching for Practice
During your studies, you will expand your personal skills profile, in terms of your technical and methodological expertise as well as your self-competence. The focus on the Master's thesis encourages creative approaches to problem solving, re-examination of perspectives and a combination of entrepreneurial and scientific thinking.
Work in the research group will help you develop teamwork skills, initiative, critical thinking and leadership skills. We promote independent, research-based learning in small classes with interactive lessons.