Internship M2 - Molecular Dynamics Simulation of Lipid NanoParticle

Laboratoire CP2M (CNRS/UCBL/CPE Lyon). UMR 5128; Villeurbanne; Sur place; EUR 12 000 - 17 000; Temps partiel

Résumé du poste

Laboratoire CP2M (CNRS/UCBL/CPE Lyon). UMR 5128 in Villeurbanne invites applications for an M2 internship on Molecular Dynamics Simulation of Lipid Nanoparticles. You will work under Fabrice Brunel and Giovanna Lollo on SAXS and MD simulations to model lipid systems.

The project aims to develop coarse-grained lipid and RNA models using MARTINI to analyze SAXS curves and assemble insights. Candidates should be pursuing a Master 2 in Polymer Chemistry, Macromolecular Chemistry, Materials

Qualifications

• Master’s Year 2 degree in Polymer Chemistry, Macromolecular Chemistry, Materials Chemistry, or a related field.
• Experience with Linux, Bash, and Python for data analysis.
• Basic knowledge of molecular dynamics and MD simulation software.
• Familiarity with soft-matter chemistry and lipid membranes.
• Strong problem-solving and communication skills.
• Interest in interdisciplinary research.

Responsabilités

• Parametrize specific ionizable lipids and RNA.
• Measure lipid membrane thickness and scattering length density profiles.
• Assess lipid membrane rigidity through lipid pulling and real-space fluctuation analysis.

Connaissances

Linux

bash

Python

MD simulations

GROMACS

soft-matter chemistry

problem-solving

communication

Formation

Master’s Year 2 degree in Polymer Chemistry

Outils

GROMACS

Description du poste

Internship M2 - Molecular Dynamics Simulation of Lipid NanoParticle

21/09/2026

28/02/2027

The intern will join the CP2M laboratory (UMR 5128, UCBL–CNRS), a research team recognized for its expertise in the physical chemistry of polymers and colloids. The intern will be supervised by Fabrice Brunel (Associate Professor, UCBL, CP2M), an expert in physical chemistry with extensive experience in SAXS and MD simulations, and co-supervised by Giovanna Lollo, an expert in LNP development. This Master’s research project is part of the LIONS project, funded by Bpifrance and the Auvergne–Rhône-Alpes Region, in partnership with the companies Xenocs and Dillico.

Description

Scientific background

Since the COVID-19 pandemic and the success of the mRNA vaccines (i.e. RNA encapsulated in Lipid NanoParticles, LNP), have emerged as an efficient delivery system for nucleic acid-based therapeutics. Gaining detailed insight into the internal structure of LNP remains a significant challenge using conventional characterization techniques such as cryo-electron microscopy and dynamic light scattering offer limited or indirect information. These limitations make it difficult to quantitatively assess structural features such as bilayer spacing, core-shell architecture, or the localization of encapsulated material.

Small-angle X-ray scattering (SAXS) overcomes these limitations by reconstructing electron density distributions within nanoparticles, enabling inference of LNP internal structure. However, identifying an appropriate structural model (e.g., bilayer or core-shell) that fits the data and yields physically meaningful results remains challenging.

In order to gain a comprehensive understanding of LNPs internal structure, SAXS experiments can be combined with molecular dynamics (MD) simulations. Among MD approaches, coarse-grained models (particularly the MARTINI force field) are especially well suited for studying LNP internal structure. The MARTINI force field is a versatile coarse-grained model for MD simulations, with available topologies covering a wide range of biomolecules such as: lipids, proteins and nucleic acid. The aim of this internship is to develop coarse-grained models of lipids and RNA to study their assembly and facilitate the analysis of SAXS curves.

Internship Objectives

• Parametrize specific ionizable lipids and RNA.
• Measure lipid membrane thickness and scattering length density profiles.
• Assess lipid membrane rigidity through lipid pulling and real-space fluctuation analysis.

Profil

Candidate profile

Education: Master’s Year 2 degree in Polymer Chemistry, Macromolecular Chemistry, Materials Chemistry, or a related field.

Desired skills

• Proficiency in Linux, bash and Python or similar for data analysis.
• Basic knowledge of molecular dynamics, experience with simulation software (GROMACS) is a plus.
• Understanding of soft-matter physical chemistry (lipid membrane, RNA and biomolecular systems).
• Strong problem-solving, communication skills and curiosity for interdisciplinary research.