KTH Royal Institute of Technology MSc Biostatistics and Data Science
KTH Royal Institute of Technology

KTH Royal Institute of Technology

MSc Biostatistics and Data Science

Stockholm, Sweden

MSc

2 years

English

Full time

Aug 2026

SEK 360,000 *

On-Campus

* for non-EU/EEA/Swiss | no tuition fee for citizens of EU/EEA country or Switzerland

Key Summary

About: The MSc Biostatistics and Data Science is a joint KTH, Karolinska Institutet, and Stockholm University programme for students with mathematics, statistics, or computer science backgrounds. It covers probability, inference, biomedical modelling, computational methods, machine learning, missing and correlated data, Bayesian inference, study design, and a research project.

Career Outcomes: Graduates have career opportunities in biomedical, healthcare, pharmaceutical, insurance, public health, and academia; work as biostatisticians, data scientists, clinical trial statisticians, or research scientists. The programme prepares students for doctoral study in biostatistics and data science and for developing or applying statistical methods to biology, medicine, and public health practice.

The master's programme in Biostatistics and Data Science offers a unique combination of Biostatistics and Data Science. Students with backgrounds in Mathematics, Statistics, Computer Science, or related disciplines are provided with the skills to solve problems in Biology, Medicine, and Public Health. The programme is offered jointly by KTH, Karolinska Institutet, and Stockholm University through the university alliance Stockholm Trio.

Biostatistics and Data Science at KTH, Karolinska Institute and Stockholm University

The first year begins with mathematically rigorous courses in statistics, exploring probability theory and statistical inference, and statistical modelling with a focus on modelling biomedical data. Additionally, you will get an introduction to computer-intensive methods in mathematical statistics. These courses give you the basis for elective courses in machine learning and statistical learning that you will take in the second half of the year. You will also get an introduction to human biology, physiology, and genetics, and an introduction to medical research, emphasising its multidisciplinary nature and the role of biostatistics and data science in medical research and society.

The second year introduces topics in biostatistical science that complicate or extend the concepts and methods covered in previous courses, for example, incomplete or missing data, correlated or clustered data, and Bayesian inference. Courses in the second year build upon previous courses by giving an overview of methods for designing and analysing medical research studies in three areas: pre-clinical studies and animal research, clinical trials, and observational studies.

In the final semester, you will conduct a degree project, which involves completing a research project in an academic setting, government authority, or industrial environment and can potentially include studies abroad.