The Data Science for Life Sciences master programme is for life science or IT students who want to learn how they can be part of the growing field of data science. After this master, you will possess the skills you need to facilitate and initiate innovations for life science, like programming machine learning applications and managing data storages. With this knowledge, you breach the gap between life sciences and computer technology.

Would you like to specialise further in Data Science? In the master programme Data Science for Life Sciences, you will be combining life sciences with data science. You will learn how to use new data processing technologies, write algorithms - for instance to recognize sick cells - and analyse health-data. These skills will help you to contribute to better and more efficient healthcare and aid innovations in the life science industry. In short, you will develop into a data scientist who bridges the gap between domains of life science and technology. You will play an active role in ensuring that the data generated by the exponential growth in databases and medical databases is exploited to the full. We train you to work as a professional data scientist, who is up to speed with new technologies and knows how and where to gather necessary information. The master is practice based, so you will spend a lot of time programming and writing computer code, and directly applying your gathered knowledge. This master programme responds to a growing demand for data scientists and is the first master at a university of applied sciences in this field.

Are you interested? 
If you want to know more about the programme you can download our course catalog or order our brochure. You can also watch this 9-minute presentation about the master. If you have any questions, you can contact us or read our FAQ.

Applicaton 

As an EU-student you can apply for this master via Studielink until August 15. If you have questions about the application requirements please have a look at this page.

Admissions are dealt by an Admission Committee. Hanze UAS will review your application and will decide whether you are accepted or not based on the admission requirements. You are asked to deliver an application file with documented proof of your knowledge and skills. You can send your documented proof to admission.dsls@org.hanze.nl.

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Curriculum

Curriculum

The master's programme is divided into three semesters. The first and second semesters focus on general and advanced skills and knowledge in the field of data science, programming, professional skills, research skills and life sciences. The focus of the master is practice based. During the first year of the programme you gain direct experience and acquire valuable insights by carrying out assignments and projects for research centres and industry. You can specialize by choosing for bioscience projects or projects from the life science industry. In the third semester, you will undertake a graduation project within your specialisation. This final project is carried out independently and individually.

Learning environment

Learning environment

As part of the learning environment, you will be working with lecturers and researchers, as well as partners from professional practice. In this manner teaching, research and professional practice reinforce each other. You will encounter challenging problems in your practice-based projects, from the very start of the programme. The outcome of the research projects and the solutions are not clear beforehand, and thus require creativity, critical sense, teamwork and knowledge creation.

International outlook

International outlook

The programme aims to facilitate students in their development into professionals with an international outlook. Students will come in contact with a lot of international oriented companies and researchers. We prepare the students for a global work environment since we offer the programme in English and organise research activities with an internationally oriented staff.

Research themes

Research themes

The focus of the master programme is mainly on health and agri-food topics:

  • Personalised medicine: collecting, integrating and analysing data to arrive at a single-patient diagnosis and treatment plan

  • Quantified self: visualisation of a person's health data in order to answer health-related questions

  • Integrated omics research: collected fields relevant for data science in life sciences (i.e. fields ending in '-omics')

Admission requirements

Admission requirements

The full admission requirements can be found in Chapter 5 of the Teaching and Examination Regulations (TER). Admissions are dealt with by the admission committee, who have the final say. You may be asked to take an additional test or tests and/or modules in the field of statistics and programming. Here we give you a short overview:

Dutch applicants:

You may be admitted if you have one of the following qualifications (or equivalent):

  • Bachelor's degree from the Institute for Life Science and Technology

  • Bachelor's degree in Medical Imaging and Radiation Therapy

  • Bachelor's degree in Communication, Media & IT from a university of applied sciences

  • Bachelor's degree in Electrical Engineering, Sensor Technology major (with the skills English, Statistics and programming)

International applicants:

  • BSc in Biology, Life Sciences, Informatics or equivalent

English level:

  • IELTS test, the required score is 6.5, with no sub scores below 6;

  • Cambridge Advanced Exam in English: B minimum; or Cambridge Proficiency Exam in English: C minimum.

  • Students holding an International or European Baccalaureate are also exempted, as are students with a previous qualification issued in the United States of America, Canada, Australia, New Zealand, Great Britain or Ireland. Finally, the exemption applies to students who hold a previous qualification issued outside the EEA if they can submit a statement from the educational institution where they took the course testifying that it was taught in English.

Entrance level:

In general, holders of a Bachelor's degree within the fields described above must deliver documented proof of knowledge and skills in the disciplines of programming, data science and biology. Demonstrated proof is either a diploma, a certificate, a portfolio or a sufficient grade of the entry test.

Tuition fees

Tuition fees

International students enrolled in one of the programmes at Hanze University of Applied Sciences, Groningen, have to pay tuition fees for each academic year that he/she is enrolled. The amount that you will be required to pay depends on your nationality, the programme you have applied for and whether you have studied in the Netherlands before. 

International student?

Click here for more information.

Dutch student? 

Click here for more information.

Scholarships

Scholarships

There here are a number of scholarships available to students at Hanze University of Applied Sciences, Groningen (Hanze UAS). Certain scholarships are funded (or co-funded) by Hanze UAS and others by the Dutch government. By providing financial support to incoming international students, Hanze UAS and its partners strive to give people all over the world access to higher education.

Click here for more information

Practical matters

Pratical matters

Moving to another country, let alone to another continent, can be a daunting endeavour. Good preparation is key in making your move run smoothly. Fortunately, the Netherlands has been a prime destination for international students for many years, meaning that you will encounter multiple institutions along the way that will help make your life easier. Click here for more information.

​​​Career opportunities

Career opportunities

Graduates of the master programme will find jobs within a wide range of fields, including ones in scientific research, industry and policymaking, such as:
• Senior scientist
• Big data engineer
• Bio-statistican
• Scientist
• Scientist researcher


Semester 1

  • Omics Project (data science for personal health)
  • Preparatory Course
  • Data Science I (exploration)
  • Programming I (design)
  • Research & Professional Skills

Semester 2

  • Omics Project (integrated omics)
  • Data Science II (modeling)
  • Data Science III (prediction)
  • Programming II (big data)
  • Research & Professional Skills

Semester 3

  • Graduation project and thesis
  • Research & Professional Skills

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