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M2 DPH-DataScience

The Master in Public Health Data Science 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. Covering multidisciplinary skills in epidemiology, informatics and statistics, the program ensures that students gain strong knowledge about the strengths and limits of digital technologies and their use in public health research.

Program Duration

1 year (60 ECTS), including an internship

Profile

Hold at least a Master (year 1) degree with honors (minimum 240 ECTS or equivalent) in one (or more) of the following disciplines: statistics, informatics or epidemiology.

Strengths

Epidemiology
› Translation of a public health/clinical problem into a research question, including the design of the research plan for surveillance systems, observational and experimental studies (i.e. clinical trials), the 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.

How to apply ?

Admission requirements:
Hold at least a Master (year 1) degree with honors (minimum 240 ECTS or equivalent) in one (or more) of the following disciplines: statistics, informatics or epidemiology.

Language requirements:
This program is taught entirely in English. Excellent proficiency in English is therefore required. Students whose native language is not English must provide a TOEFL or IELTS certification:  TOEFL score of 550/213/79-80 or IELTS score of 6.0.

Documents necessary for the selection procedure:

- Official transcripts, copies of all previous diplomas
- Passport copy (or ID card if European)
- Copy of birth certificate (if non-European)
- Cover letter and CV (in English)
- Professional project and experience
- Language test (ECTS, TOIEC, IELTS…) or certificate of studies in an English speaking High School

Please note:
Maximum number of students: 15
Selection: based on documents and an interview

And After ?

Upon completion of this Master in Public Health Data Science, students may continue with further studies and research via a PhD in Digital Public Health or they may enter the working world with strong qualifications for a career in public health. Graduates not only have a global vision of data science issues in relation to epidemiology and public health, they also master the research and leadership skills that are necessary for chief data officer jobs. They are thus well prepared to become future leaders of the digital public health domain within the public and / or private sector.

Programme Structure

Semester 3

Basics (6 ECTS)
Focus on basic knowledge and the functional capabilities of the tools used in health data analytics.
Electronic health data (6 ECTS)
Focus on the skills required to conceptualize, manage, analyze and communicate via health research carried out by Electronic Health Records (HER) and medicoadministrative databases (MA-DBs).
Digital cohorts (6 ECTS)
Focus on the skills required to conceptualize, manage, analyze and communicate via cohort studies that integrate digital tools.
Web-based data (6 ECTS)
Focus on the abilities needed to prepare Public Health studies which integrate data from social networks and web forums, linked open data and mobile data. Practice is carried out via a dedicated case study that involves the processing of large mobile dataset (call details records).
Omics data (6 ECTS)
Focus on the abilities needed to conceptualize, manage, analyze and communicate using clinical studies that integrate high dimensional data.


Semester 4 

Value creation (6 ECTS)
This final course prepares students so that as graduates, they are capable of becoming immediate contributors in the workplace whether it be in the academic or the industrial sector.
Students learn to develop their entrepreneurial skills and also acquire an understanding of the societal and economic value created by digital public health data research.
Internship (24 ECTS)
Students may complete their internship either with the research team that generated a project case study during the Public Health Data Science Master program or else with a new team from the extensive research network of the Graduate Program.