Public Health Data Science
This international Master program provides a year of international research into public health data science, from project design to real life health data analysis and the communication of results.
Quick Facts
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Duration: |
1 year (60 ECTS), including an internship |
Starting Date: |
The academic year generally starts end September/early October and finishes end May the following year |
Tuition Fee: |
Annual registration fees for all selected applicants are calculated according to the rules and regulations of the University of Bordeaux. Please consult the Admission & Financing section and/or the University of Bordeaux website for specific details. |
Location: |
University of Bordeaux |
Program outline
The Master in Public Health Data Science provides a year of international research in public health data science, from project design to real life health data analysis and the communication of results.
Selected within the French “Investments for the Future” program as an “Initiative of Excellence”, the program covers multidisciplinary skills in epidemiology, informatics and statistics, and ensures that students gain strong knowledge about the strengths and limits of digital technologies and their use in public health research.
Strengths
Epidemiology
Translation of a public health / clinical problem into a research question, including the design of research plans for surveillance systems, observational and experimental studies (i.e. clinical trials), evaluation of validity and causality of an association.
Statistics
- Methods for supervised and unsupervised statistical analysis and modelling of biomedical data (including high-dimensional and time-to-event data), statistical learning, data mining, data integration, advanced computational statistics.
Informatics
- Architecture of data integration (i2b2, Transmart), interoperability, knowledge representation (terminologies, ontologies), natural language processing, data visualization, programming, cloud computing and Hadoop, linked open data, security, confidentiality and integrity of data.