Stage M2: AI-Driven Mapping of Microprotein Structures

SFBI; Gif-sur-Yvette; On-site; EUR 12,000 - 18,000; Part time

Benefits offered by this job

HPC/GPU resources

Mentorship from researchers

Job summary

SFBI in Île-de-France seeks an M2 internship to map the structural space of microproteins using deep learning. You will work with ESMFlow and MD trajectories to predict stable conformations from noncoding sequences, advancing understanding of these small proteins.

The project blends ML, molecular dynamics, and evolution, with access to HPC/GPU resources and close supervision from researchers. Ideal for early-career scientists.

Qualifications

• Programming in Python is mandatory.
• Interest in machine learning and structural biology is essential.
• MD simulations or protein-structure analysis experience is a plus.

Responsibilities

• Learn from MD to identify stable conformations and assess persistence.
• Extract descriptors of conformational persistence and train ML models.
• Rank candidate structures for microproteins arising from noncoding sequences.
• Explore protein-language models or structural embeddings if progress allows.

Skills

Python

Machine learning

Structural biology

Education

M2 / Master 2 in Computational Biology

Tools

MD simulations

Protein structure analysis

Job description

SFBI in Île-de-France seeks an M2 internship to map the structural space of microproteins using deep learning. You will work with ESMFlow and MD trajectories to predict stable conformations from noncoding sequences, advancing understanding of these small proteins.

The project blends ML, molecular dynamics, and evolution, with access to HPC/GPU resources and close supervision from researchers. Ideal for early-career scientists.