Program Overview

Program Overview

The M2 Genomics Informatics Mathematics and Artificial Intelligence for Health and Environment (GENIOMHE) is a multidisciplinary training program that allows students to understand the complex and diverse challenges of biology in order to meet current research and innovation needs in academic research, the biotechnology industry, the pharmaceutical industry, and health.

Objectives

This master's degree program aims to:

• Evaluate and optimize the various computer and statistical methods that are to be implemented in the analysis of genomic Big Data, particularly in the context of precision medicine.
• Meet the new challenges related to precision medicine made possible by the rapid and massive production of genomic data.
• Meet the challenges of using artificial intelligence in the health fields.
• Master biomedical data analysis and modeling techniques.
• Be autonomous in managing application development projects in various programming languages, and propose innovative IT solutions.

Skills

The program enables students to:

• Evaluate and optimize the various computer and statistical methods that are to be implemented in the analysis of genomic Big Data, particularly in the context of precision medicine.

Career Opportunities

Career prospects include:

• Researcher or teacher-researcher after a doctorate
• Data scientist
• Expert in data science
• Expert in data management
• Platform manager
• Bioinformatics engineer (Research and Development)
• Data scientist after a master's degree
• Specialist in artificial intelligence (IA) after a master's degree
• Research engineer or study engineer
• Teacher-researcher (after a doctorate)
• Data scientist
• Consultant

Further Study Opportunities

Further study opportunities include:

• Doctorate in Bioinformatics
• Specialized master's degree
• Advanced data analysis, artificial intelligence, or machine learning
• Data scientist, data analyst, or machine learning engineer in innovative sectors (tech, finance, health, energy, etc.)
• Researcher or expert in modeling and data analysis in companies or leading laboratories
• Project or mission manager

Fees and Scholarships

The amounts may vary depending on the program and personal circumstances.

Admission

Capacity

• Available places: 25

Public and Prerequisites

The program is aimed at students who have validated a master's degree in bioinformatics (M1 GENIOMHE-AI or other) or a monodisciplinary master's degree in computer science or biology with proven skills and real motivation for bioinformatics.

Application Period

• From January 15, 2026, to July 15, 2026

Supporting Documents

Compulsory Supporting Documents

• Motivation letter
• All transcripts of the years/semesters validated since the high school diploma at the date of application
• Certificate of English level
• Selection sheet for continuation in M2
• Curriculum Vitae
• Detailed description and hourly volume of courses taken since the beginning of the university program

Additional Supporting Documents

• VAP file (obligatory for all persons requesting a valuation of the assets to enter the diploma)
• Residence permit stating the country of residence of the first country
• Or receipt of request stating the country of first asylum
• Or document from the UNHCR granting refugee status
• Or receipt of refugee status request delivered in France
• Or residence permit stating the refugee status delivered in France
• Or document stating subsidiary protection in France or abroad
• Or document stating temporary protection in France or abroad

Program Details

The program consists of a set of teaching units organized into several blocks:

• Advanced Genomics
• Computer Science for Big Data
• Data Science and Artificial Intelligence for Precision Medicine
• Computational Systems and Structural Biology Optional teaching units will also be offered, such as an introduction to entrepreneurship.

Location

• EVRY

Research Areas

The program covers various research areas, including:

• Genomics
• Bioinformatics
• Artificial intelligence
• Precision medicine
• Biomedical data analysis and modeling
• Computational systems and structural biology