Master's in Epidemiology and Biomedical Data Science
Epidemiology and Biomedical Data Science
Degree title
Study places
Duration of studies
Scope
Teaching method
Next application period
Top reasons to study Epidemiology and Biomedical Data Science
- A unique study programme that combines epidemiology with data analysis – a global interest and demand for expertise exists. The curriculum is balanced to focus on both Epidemiology and Biomedical Data Science.
- Research-oriented programme provides meaningful thesis topics with an intention to educate new researchers to the field.
- The University of Oulu has an impressive history in studying longitudinal factors affecting the population on a large-scale using birth cohorts.
- Courses are participatory by nature that encourage discussion, taught by friendly teaching staff.
- Programme offers an international classroom - a mix of students with diverse backgrounds, some beginning their career, others already having gained experience in the medical sector.
EBDS is very research-oriented with the goal of training future researchers in the field. An important part of the multidisciplinary programme is the development of and training in statistical and biostatistical approach for medical research. The programme is much more involved in epidemiological methodology and in very large data analysis when compared to similar programmes.
"The knowledge gained will help graduates to better understand the complex bio-psychosocial aetiology of chronic diseases, i.e. obesity, type-2 diabetes, depression, and emergent epidemics, like Covid-19."
The ability to collect, manage and analyse data from different sources and translate the research into solutions for public health needs is going to be very useful in the future and will lead to many exciting and varied career opportunities, both in academia and in the public and private sectors.
You are a great fit for our programme if
The ideal candidate is academically grounded in health or quantitative sciences, with a Bachelor’s degree in fields like public health or biology. They are intellectually curious, research-driven, and eager to harness extensive life-course data for public health advancements.
This individual is a collaborative communicator, capable of articulating complex data insights and translating them into actionable health solutions. They are ready to contribute to the understanding of diseases and to innovate in the face of global health challenges.
Admissions criteria
University level Bachelor’s (or higher) degree in public health, global health, statistics, biology, genetics, ecology, epidemiology, bioinformatics. The programme will open also to medical doctors, dentists as well as health scientists with a master's degree.
Read about eligibility and admissions procedure for this programme, detailed information available at Studyinfo.
Core skills and competence
After completing the Master's Degree, the student is able to:
- Collect and manage data
- Identify and integrate multiple sources of data
- Analyse and interpret data
- Interpret causal and non-causal relationships
- Conduct research work independently and in teams by using scientific research methods
- Communicate research findings orally and in writing clearly and analytically
- Broaden and deepen one’s know-how independently, in view of life-long learning.
Programme structure and courses
For detailed information about courses and the programme structure, take a look at the study guide:
See study guide for Epidemiology and Biomedical Data Science programme structure and courses
Occupational profiles of the graduates
- Community Health Worker
- Environmental Scientists and Specialists
- Field Investigator
- Health Department Administrator
- Health Education Specialist
- Health Services Manager
- Data Scientist
- Minority Health Administrator
- Research Coordinator.
Exceptional data set at students' use
Students will train with one of the largest collections of real life-course data and biobanks, which means they will have an exceptionally rich set of socio-demographic, health and multi-omic data at their use.
