Cheminformatics Researcher Role:
- Develop and optimise molecular representations for lipids involved in targeted lipid nanoparticles (tLNPs).
- Analyse lipid structures using cheminformatics workflows, AI/ML methods, and public/internal datasets.
- Generate and refine virtual lipid libraries using chemical intuition, molecular modelling, and reaction-based enumeration strategies.
- Build and validate predictive models linking lipid structure descriptors to formulation and in-vivo outcomes.
- Design workflows for diversity selection and prioritisation of lipids for synthesis and chemical space exploration.
Your Background:
- PhD in Cheminformatics, Computational Chemistry, or a related scientific discipline with relevant industry or research experience.
- Strong experience applying cheminformatics and AI/ML techniques to lipid analysis and molecular design.
- Proven scientific programming capability, particularly with Python.
- Understanding of lipid nanoparticle formulation, synthesis, purification challenges, and structure-property relationships would be advantageous.
- Experience with chemoinformatics toolkits, molecular descriptors, and AI-enabled computational chemistry approaches.