Master's Programme in Biostatistics and Data Science
In this two-year master's programme, offered jointly by Karolinska Institutet, KTH Royal Institute of Technology, and Stockholm University, you will learn the key skills required to work as a biostatistician or data scientist. You will get training in statistics, computational science, and programming, along with the theoretical and practical education to apply these skills to challenges in biology, medicine, and public health. In addition, you will learn the analytic techniques used in data science to prepare you for the data-driven challenges of modern medical research and a career as a data scientist. During your two years in Stockholm, you will study a tailored selection of courses from three universities with prominent research in their respective fields: Karolinska Institutet, KTH Royal Institute of Technology, and Stockholm University.
The programme is delivered by a team of teachers who are internationally recognised for their research in developing new biostatistics and data science methods, and for their collaborative research with scientists from other disciplines to improve health outcomes.
The first year begins with rigorous courses in statistics, exploring probability theory and statistical inference, and statistical modelling with a heavy 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 participating in research projects in an academic or industrial environment.
The programme is two years long, so comprises 120 credits (ECTS). Of this, 60 credits are mandatory courses (eight courses, of which two are at Stockholm University, two at KTH and four at Karolinska Institute), 30 credits are elective courses (half of these in the second semester and half in the third semester), and 30 credits are the degree project, which you do at Karolinska Institute.
Year 1
In the autumn of the first year, you take these two courses at Stockholm University:
Theory of Statistical Inference (MT5017)
Classification and Analysis of Categorical Data (MT5022)
Alongside these you take courses in probability theory and biostatistics at KTH and Karolinska Institute.
During the spring you take a mandatory course at Karolinska Institute, and a mandatory course at KTH, and two conditionally elective courses at KTH or Stockholm University.
Year 2
During the third semester you take two mandatory courses at Karolinska Institute, and two conditionally elective courses at KTH or Stockholm University. See links above, under year 1.
During the last semester of the programme you conduct a degree project.
Admissions for the programme is handled by KTH Royal Institute of Technology, and you apply via Universityadmissions.se. Please note that application is only open in the first admissions round, from mid-October to mid-January.
Entry requirements, application documents and selection (kth.se)
Housing for international students
Tuition-paying students are welcome to apply for university housing via Stockholm University.
More information and housing application for international students
The combination of biostatistics and data science gives graduates an excellent profile for challenging and rewarding careers in industry (for example, biomedical, healthcare, insurance, and pharmaceutical sectors), government (for example, public health agencies) and academia. There is a shortage of trained biostatisticians and data science professionals, both in Sweden and internationally. After graduating from this programme, you will find excellent opportunities for doctoral studies, both in developing new biostatistics and data science methods and applying your knowledge and skills in biostatistics and data science to address research topics in biology, medicine, and public health.
Programme director (at Stockholm University): Tom Britton
Programme administration and advice (at Stockholm University): studievagledning@math.su.se
