ML Internship: Interpretable Dynamics for Cell States

SFBI; Montpellier; On-site; EUR 7,800 - 13,000; Full time

Job summary

SFBI in Montpellier invites students in mathematics, CS or ML to an internship focused on machine learning for cell dynamics in biomedicine.

The project covers variational autoencoders, probabilistic modelling, and dynamical systems to understand cell-state transitions and responses to perturbations.

Location is Montpellier, France; deadline 15 November 2026; host teams LPHI, CNRS, INSERM and IGF collaborate.

Qualifications

• Must be a student in related fields.
• Interest in biomedicine and single-cell data.
• Experience with Python and ML is beneficial.

Responsibilities

• Develop ML methods based on VAEs for cell dynamics.
• Reconstruct dynamical systems from high-dimensional gene data.
• Collaborate with host and partner teams at LPHI and IGF.

Skills

Applied mathematics

Computer science

Machine learning

Education

Student in applied mathematics, CS, or ML

Tools

Variational Autoencoders

Job description

SFBI in Montpellier invites students in mathematics, CS or ML to an internship focused on machine learning for cell dynamics in biomedicine.

The project covers variational autoencoders, probabilistic modelling, and dynamical systems to understand cell-state transitions and responses to perturbations.

Location is Montpellier, France; deadline 15 November 2026; host teams LPHI, CNRS, INSERM and IGF collaborate.