Master of Science in Life Sciences - Applied Computational Life Sciences
Life Scientist or Data Scientist? With us, you combine both!
AI, algorithms, and digital twins are transforming the life sciences. Those who master these disciplines stay one step ahead in the job market. Develop THE innovations that will shape a better future - together with our research groups and in collaboration with leading industry partners.
Why pursue a Master’s degree in Applied Computational Life Sciences?
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.
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.
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.
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.
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.
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.
Your background
You have a bachelor’s degree in the life sciences or a related field. Other degrees may also be accepted. We are happy to advise you.
"At the University Hospital Zurich, a new data science project is initiated almost every week. For example, attempts are being made to use data analytics to gain new insights for the treatment of patients or to use AI models to calculate forecast probabilities for diagnoses. The solid understanding of data acquired during my studies helps me in my daily work with highly sensitive data, be it in the development of database interfaces or in the programming of various applications for data transformation and integration."
Matthias Joos, Graduate and Data Solution Engineer at the University Hospital Zurich
Career: What a Master’s degree in Life Sciences in Applied Computational Life Sciences will allow you to do.
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.
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Good reasons for a Master’s study in Wädenswil
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.
Study programme and course content
Your studies include three areas of competence plus a Master's thesis, with a total of 90 credits (ETCS).
Based on your interests, before starting your studies you will work out your own personal learning objectives with your specialisation director and your supervisor. You will define the topic for your Master's thesis and design your own personal study path from the range of available modules.
Based on the topic of your Master's thesis, you will be assigned to a corresponding specialisation module that will fully prepare you for your Master's thesis. While working on your Master's thesis, you will be part of a research group that is working closely with our business partners or doing research at one of our institutes.
Here you will learn systematically from scratch how to code small to medium-size programs using the programming language Python. You will be introduced to data structures and acquire algorithmic thinking.V5_1 is part of the “Specialisation Skills” in the ACLS Master’s Specialisation that are taught on our campus in Wädenswil on Mondays and Tuesdays.
In this module you will learn how to mathematically describe and model life science problems with mechanistic approaches such as partial differential equations and stochastic methods such Markov-chain Monte-Carlo algorithms. V5_2 is part of the “Specialisation Skills” in the ACLS Master’s Specialisation that are taught on our campus in Wädenswil on Mondays and Tuesdays.
In this module appropriate lecturers are assigned to optimally prepare you for your master’s thesis. Depending on the field of your master’s thesis topic, you will either take the Specialisation Track Module 1 in the “Active Module”-, the “Genome Oriented”-, the “Process Oriented”- or the “Special”-Track. V5_3 is part of the “Specialisation Skills” in the ACLS Master’s Specialisation that are taught on our campus in Wädenswil on Mondays and Tuesdays.
In this module you will learn system theory and how it is applied to real-world problems using mathematical tools and Monte-Carlo simulations. CO1 is part of the “Cluster-specific Modules” of our cluster Bio-Engineering and Computational Sciences that are taught in collaboration with other Universities of Applied Sciences in Olten on Wednesdays.
This module provides you with the knowledge of the state of the art machine learning techniques and how to apply them to problems in the life sciences and in biomedical engineering. BECS2 is part of the “Cluster-specific Modules” of our cluster Bio-Engineering and Computational Sciences that are taught in collaboration with other Universities of Applied Sciences in Olten on Wednesdays.
In D1 you will get an introduction to databases, and you will learn how to handle data using the R software. Specifically, you will learn how to clean data, understand and apply the grammar of graphics, design plots, and explore data. D1 is the basis for D2 “Design and Analysis of Experiments” and D3 “Modelling and Exploration of Multivariate Data”.D1 is part of “Core Competences” that are taught in collaboration with other Universities of Applied Sciences. Central teaching takes place on Fridays in Olten (autumn semester) or Fribourg (spring semester) and local coaching on Tuesday mornings in Wädenswil.
In D2 you will learn the basics of statistical inference, the design of experiments (such as randomization and blocking), perform statistical analysis and report findings scientifically. D2 is part of “Core Competences”, that are taught in collaboration with other Universities of Applied Sciences. Central teaching takes place on Fridays in Olten (autumn semester) and local coaching on Tuesday mornings in Wädenswil.
In D3 you will learn how to use multiple regression models, perform model selection and explore, describe, interpret and visualise multivariate data. D3 is part of “Core Competences” that are taught in collaboration with other Universities of Applied Sciences. Central teaching takes place on Fridays in Olten (autumn semester) or and local coaching on Tuesday mornings in Wädenswil.
This module is to provide the you with a working knowledge of current artificial neural network (ANN) and deep learning (DL) techniques and apply them to problems in the field of life sciences.
This module teaches you the advantages and disadvantages of different ANN and DL architectures and corresponding applications and how to adapt and apply suitable ANN and DL techniques to problems in life sciences. It builds on «Introduction to Neural Networks»
The module covers the techniques and structures used to efficiently store, process, and load data in databases.By completing the module, students will specifically acquire knowledge and skills in the following fields: Terminology and general basics of databases and data architecture systems, Relational databases and SQL, Python/R and SQL.
Building on the module «Relational Databases» this module goes beyond by introducing different types of databases and their concepts, Data Warehouses, NoSQL database concepts, Graph-based databases. Hands-on exercises and examples will strengthen the your competences in applying database concepts in the fields of life sciences.
In this module specialist lecturers are assigned to optimally prepare you for your master’s thesis. Depending on the field of your topic, you will either take the Specialisation Track Module 2 in the “Active Module”-, the “Genome Oriented”-, the “Process Oriented”- or the “Special”-Track. V5_7 is part of the “Specialisation Skills” in the ACLS Master’s Specialisation that are taught on our campus in Wädenswil on Mondays and Tuesdays.
The course encompasses four chapters in software engineering, including basic principles of software development (requirement engineering, development models, testing), system design (OO design), design patterns (patterns and architecture), and best practices (machine learning as software, web applications, cloud computing).
The main goal of the course is to familiarise the students with software as a product and not as a piece of code that will be run once and then forgotten. As software developers or programmers, we have two types of users: the actual end user of the final code – someone who will install and run the tool/service to get results – and the code users – other engineers/programmers who will have to interact/extend/maintain the codebase. We want code to be sustainable: we spend a lot of time on the code, and it would be a shame if our work is deleted when we leave a team because no other person can understand and maintain the code. We also want code to be usable: the perfect tool is useless if no one can install and run it without special training/knowledge.
In this elective module we will deal with important and classical papers that are – in a broad sense – relevant for the field of computational life science.V5_8 is part of the “Specialisation Skills” in the ACLS Master’s Specialisation that are taught on our campus in Wädenswil on Mondays and Tuesdays.
In this module you will learn how to explain and validate different optimization methods and apply them appropriately to problems in your field. BECS4 is part of the “Cluster-specific Modules” of our cluster Bio-Engineering and Computational Sciences that are taught in collaboration with other Universities of Applied Sciences in Olten on Thurdays.
In this course you will learn how to apply image processing methods to basic image analysis problems and to understand the typical image processing chains on clinical applications. You will also get to know some advanced image processing methods.BECS3 is part of the “Cluster-specific Modules” of our cluster Bio-Engineering and Computational Sciences that are taught in collaboration with other Universities of Applied Sciences in Olten on Wednesdays.
As ACLS student you belong to the Bio-Engineering and Computational Sciences cluster. However, there is also a long list of interesting modules you can take from other clusters such as Pharmaceutical Biotechnology (BP1-BP6), Chemistry for the Life Sciences (C1-C5), Natural Resources Sciences (E1-E6), Food and Beverage Innovation (F1-F5). These modules are so-called “Cluster-specific Modules” that are taught in collaboration with other Universities of Applied Sciences at several locations in Switzerland, depending on the specific module. They are usually taught on Thursdays.
Increase your business knowledge and intelligence with elective modules covering administration, management, innovation, politics and more. B1-B4 are part of “Core Competences”, that are taught in cooperation with other Universities of Applied Sciences. Central teaching takes place on Fridays in Olten (autumn semester) and local coaching on Tuesday mornings in Wädenswil.
The Master Thesis can be written in collaboration with a partner from industry or with an academic research group. You will choose the field of your thesis and your supervisor before starting your studies at ZHAW. This enables good support by your thesis supervisor and an optimal preparation on the basis of the Specialisation Track Modules 1 and 2. If you are already curious about possible theses, then you may browse a collection of theses in our marketplace. You can also contact supervisors from the marketplace or the head of the ACLS specialisation for advice or to discuss your own ideas. The master’s thesis is completed in one semester, however if you study part-time, it may be carried out over more than one semester.
Familiarity with basic programming in Python is required. Familiarity with Keras/Tensorflow is an advantage. Most exercises will be in PyTorch/Keras/Tensorflow.These modules are so-called “Cluster-specific Modules” that are taught in collaboration with other Universities of Applied Sciences at several locations in Switzerland, depending on the specific module. They are usually taught on Thursdays.
Purple: 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).
During your studies, you will expand your personal skills in technical expertise, and 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.
Theses Interesting research questions are created with partners from industry and retail. Our graduates have already developed interesting, relevant and viable answers and solutions in their work.
