Master Data Management in Biosciences
Training future professionals in the fields of data management, from data collect to data mining.
Students will also go through quality control, splicing, data analysis and other aspects of data processing in the field of biosciences with a strong human and ethic formation.
Vous êtes étudiant français ou d’un pays membre de l’espace économique européen et souhaitez postuler en Master management des entreprises, accédez directement à l’espace de candidature via la plateforme Mon Master
For who ?
Students in bachelor third year in life sciences, digital sciences, health or any other related program
Students are given the opportunity to pursue their studies either by attending full time classes « formation initiale » or having a part time working experience called « alternance » (M1 and M2). This part time working experience can be chosen during the two years of master or only the second year of master
Classes are mainly taught in English
Appetences required :
Data and Informatics
Soft Skills
Professionalization
Biosciences
Intercultural and social differences sensitivity
Interdisciplinarity
Why Should I choose this Master Data Management in biosciences ?
Training future professionals in the fields of data management in biosciences
- Data collect
- Data mining
- Quality control
- Splicing
- Data Analysis
- Hard Data Management
- Strong Human, ethic and deontological sensibility
What job after this Master ?
The Master Data Management in Biosciences prépares our students to many jobs such as :
- Biostatictician
- Bioinformatician
- Data analyst
- Data Manager
- Project coordinator in health
- Clinical assay coordinator
You can work in many fields, such as :
- Health organisations
- Pharma industry
- Economy and agrofood industry
- Clinical research
- Environment
- Public health institutions (ARS, HAS, ANSM)
- Life and health companies
Program
MASTER 1
MASTER 1 – Full Time Class
| Semestre 1 | |
| BCC 1 – Biosciences | 7 crédits |
| Cellular and Molecular Biology of Diseases | 4 |
| Biostatistics I | 3 |
| BCC 2 – Data Sciences | 8 crédits |
| Bioinformatics I | 4 |
| Databases I | 4 |
| BCC 3 – Communication and Management | 7 crédits |
| Project Management | 3 |
| Languages | 2 |
| Communication Tools / Dataviz | 2 |
| BCC 4 – Probability and Statistics | 3 crédits |
| Probability and Statistics | 3 |
| BCC 5 – Remediation – Elective Course (Cours optionnels) | 5 crédits |
| Basics in Cellular and Molecular Biology (for students from Computer Sciences background) | 5 |
| Algorithms (for students from Life and Health Sciences background) | 5 |
| Semestre 2 | |
| BCC 1 – Biosciences | 5 crédits |
| Scientific Method | 2 |
| Biostatistics II | 3 |
| BCC 2 – Data Sciences | 15 crédits |
| Bioinformatics II | 4 |
| Object Oriented Programming | 3 |
| Data Structure and Complexity | 4 |
| Databases II | 4 |
| BCC 3 – Communication and Management | 4 crédits |
| Regulations and Laws | 2 |
| Languages | 2 |
| BCC 6 – Professionnalization | 6 crédits |
| Pathway 1 : research oriented | |
| Project in data management in biosciences (Internship) | 3 |
| Thesis (Research Thesis) | 3 |
| Pathway 2 : industry oriented | |
| Project in data management in biosciences (Apprenticeship) | 3 |
| Report | 3 |
MASTER 2
MASTER 2 – Full Time or Part Time Class
| Semestre 3 | |
| BCC 1 – Biosciences | 5 crédits |
| Introduction to translational research and clinical trials | 3 |
| Advances in Biosciences – Seminars I | 2 |
| BCC 2 – Data Sciences | 13 crédits |
| Applied Biotechnologies I | 3 |
| Operational tools for data management in biosciences | 4 |
| Introduction to AI & Machine Learning | 4 |
| Mechanisms of Data protection | 2 |
| BCC 3 – Management and Communication | 12 crédits |
| Innovation Management | 3 |
| European Environment and Policies in life sciences and public health | 3 |
| Responsible Research and Innovation | 3 |
| Languages | 3 |
| Semestre 4 | |
| BCC 1 – Biosciences | 5 crédits |
| Methodology of epidemiologic studies | 3 |
| Advances in Biosciences – Seminars II | 2 |
| BCC 2 – Data Sciences | 13 crédits |
| Applied Biotechnologies II | 3 |
| System and data management in biosciences | 4 |
| Data Mining in biosciences | 3 |
| Data Model – Big data | 3 |
| BCC 3 – Communication and Management | 5 crédits |
| Communication Techniques | 2 |
| Languages | 3 |
| BCC 6 – Professionnalization | 7 crédits |
| 3 Pathways | |
| Research internship | 7 |
| Industry internship | 7 |
| Apprenticeship | 7 |
RESPONSABLES PÉDAGOGIQUES
