AI Apprentice for RNA Knowledge Graph (Toulouse, On-site)

Evotec WD; Toulouse; Sur place; EUR 10 044 - 13 392; Plein temps

Résumé du poste

Evotec is seeking an Apprentice in AI to contribute to building an RNA-focused Knowledge Graph for therapeutic target prioritization at their Toulouse site. You will participate in sourcing RNA data, designing a Neo4j-based graph, and developing Python data pipelines to integrate diverse biological datasets.

The role involves harmonizing data, crafting graph queries, and linking the graph with the internal RNA druggability assessment platform, under guidance and rigorous scientific standards.

Qualifications

• Strong interest in bioinformatics, data integration, and scientific software development.
• Good programming skills in Python.
• Knowledge of SQL and database technologies.
• Interest in graph databases and knowledge representation.
• Familiarity with Neo4j is a plus.
• Understanding of molecular biology, genomics, transcriptomics, or RNA biology is advantageous.
• Experience with Git and collaborative software development practices.
• Strong analytical mindset, autonomy, and scientific rigor.
• Professional English proficiency is a plus.

Responsabilités

• Identify and evaluate relevant RNA data sources.
• Design and implement an RNA Knowledge Graph using Neo4j.
• Develop Python pipelines to extract, transform, and integrate heterogeneous biological datasets.
• Harmonize and validate integrated data.
• Develop graph queries and analyses to support RNA target prioritization.
• Integrate the Knowledge Graph with the internal RNA druggability assessment platform.
• Contribute to technical decisions and project documentation.

Connaissances

Python

SQL

Graph databases

Neo4j

Git

English

Formation

Bioinformatics degree in progress

Outils

Neo4j

Description du poste

Evotec is seeking an Apprentice in AI to contribute to building an RNA-focused Knowledge Graph for therapeutic target prioritization at their Toulouse site. You will participate in sourcing RNA data, designing a Neo4j-based graph, and developing Python data pipelines to integrate diverse biological datasets.

The role involves harmonizing data, crafting graph queries, and linking the graph with the internal RNA druggability assessment platform, under guidance and rigorous scientific standards.