Artificial Intelligence and Data Analysis (AIDA)

Interdisciplinarity is a fundamental pillar for scientific advancements in the 21st century. Revolutions in biotechnology and advancements in artificial intelligence now allow the generation and processing of massive volumes of data in molecular and cellular biology. It has become essential for new generations of scientists to develop interdisciplinary skills in life sciences and data analysis to effectively leverage and interpret this complex data. The M2 program in Artificial Intelligence and Data Analysis (AIDA) aims to train experts at the intersection of life sciences and artificial intelligence for data analysis.

This program is designed for individuals with an initial background in life sciences who wish to develop interdisciplinary skills in data analysis and artificial intelligence. Admission requires a Bachelor's degree in life sciences and a strong interest in data analysis and artificial intelligence methods.

Ideally, candidates are also expected to have some foundational programming knowledge. The M1 courses "Advanced Python Programming for Biology" (MU4BI033) and "Tutored Project in Systems Biology" (MU4BI034) prepare students to undertake this training. Completing an M1 internship related to complex data analysis is also recommended.

The M2 AIDA program includes the following courses:

Third Semester (S3)

• Artificial Intelligence and Deep Learning (6 ECTS): This course aims to train students in the design and application of neural networks for developing predictive models in gene expression data analysis. Special focus will be placed on using the Keras programming library (available in R and Python) to propose and implement various neural network architectures, allowing students to evaluate classification model performance on transcriptomic data from patients. The course comprises lectures, workshops, and group projects.

• Statistics for Genomic Data Classification and Mining (6 ECTS): This course provides an introduction to methods for analyzing genomic data, focusing on supervised and unsupervised classification techniques. Through lectures and projects, students learn to apply these methods to genomic datasets, with particular emphasis on integrative transcriptional network analysis.

• Single-Cell Transcriptomic Data Analysis (6 ECTS): This course offers an in-depth exploration of single-cell transcriptomic data analysis methods. Students are trained in the critical stages of data interpretation, from preprocessing to result analysis. Group projects allow students to apply their knowledge to real-world biological challenges.

• BMC Disciplinary Courses (12 ECTS): AIDA students can choose from a selection of courses to enhance their skills in molecular and cellular biology, totaling 12 ECTS from BMC offerings in areas such as immunology, genomics, and molecular biology. Options include:

  • Immunology: AIDA students may specialize in immunology through courses on transcriptomic data analysis, high-dimensional cytometric data analysis, experimental design with immunomonitoring tools, and systems immunology lectures (taught exclusively in English).

  • Genomics: AIDA students may specialize in genomics with courses in evolutionary genomics, human genetics, and medical genomics (taught exclusively in English).

  • Molecular Biology: AIDA students may specialize in molecular biology through courses in biochemistry, genetics, and proteomics, with a focus on cheminformatics or protein folding (taught exclusively in French).

Fourth Semester (S4)

• Internship (30 ECTS): The M2 program concludes with a six-month internship in a research lab (public or private) or a company, providing students with the opportunity to apply their skills and knowledge in a professional context. Starting early in the year, students receive support in their internship search. The internship requires a written report and an oral defense.

The AIDA program aims to develop both disciplinary and transferable skills, enabling students to master data analysis tools and methods in contexts rooted in molecular and cellular biology themes.

Disciplinary Skills

• Strengthen expertise in molecular and cellular biology.
• Master concepts related to the generation of large-scale data through biotechnological tools.
• Master statistical tools and analytical approaches to interpret complex biological data.
• Gain expertise in supervised and unsupervised learning methods.
• Apply deep learning approaches and quantify model prediction accuracy.

Transferable Skills

• Interpret complex biological data in an interdisciplinary context.
• Develop critical thinking in evaluating experimental results and the methods used.
• Carry out scientific projects, from design to result analysis.
• Work effectively in teams while also managing projects independently.
• Communicate results clearly to both technical and non-technical audiences.
• Develop a personal and professional project linked to artificial intelligence and biological data analysis.

The AIDA program offers a variety of career opportunities in modern biology by integrating skills in data analysis and molecular and cellular biology. Graduates are in high demand in the biotechnology, biomedical, pharmaceutical, and academic sectors.

• Careers in Modern Biology: Modern biology is rapidly evolving with the emergence of new tools and technologies, including genomic sequencing, computational biology, and synthetic biology. Graduates can pursue roles as researchers, bioinformaticians, biological engineers, or experts in biotechnology regulation and development.

• Data Scientists in Biology: With the increase in available biological data (genomics, transcriptomics, proteomics, imaging, etc.), data scientists play a crucial role in analyzing and interpreting these data. They use algorithms and predictive models to advance scientific knowledge, from basic research to personalized medical treatments.

• Digital Transformation Leads in Biology: These professionals integrate digital technologies into biotech companies and research labs. They manage the implementation of infrastructure for large-scale biological data processing and train teams in the use of modern tools.

• Pursuing a Ph.D.: Graduates of the BMC-AIDA Master’s who wish to deepen their scientific expertise can pursue a Ph.D. This pathway opens doors to careers in academic or industrial research, covering a range of topics from fundamental biological mechanisms to applications in systems biology and artificial intelligence.

This program is accessible starting from the first year of the BMC Master’s or directly in the second year, depending on the application evaluation.

Applications for the first year of the BMC Master’s at Sorbonne University are submitted via the Mon Master platform (https://www.monmaster.gouv.fr/). Applications for the second year of the AIDA-BMC Master’s program are submitted via the e-candidat platform (https://candidatures-2024.sorbonne-universite.fr/#!accueilView, for candidates from a French institution) or through Études en France (https://www.campusfrance.org/fr/candidature-procedure-etudes-en-france, for international students).