An experienced computational chemist specialised in molecular modelling using both commercialised software (e.g. Schrodinger) and open-source ones (e.g. Gromacs). An application scientist working in generative pipelines side-by-side with chemists and biologists to deliver hit-to-lead optimization. Over 10 years' experience in Molecular Dynamics Simulations. Experienced in applying machine learning techniques to ligand analysis. Excellent track record of publications and scientific presentations.

CORE SKILLS/STRENGTHS
• Molecular modelling using Schrodinger software (e.g. FEP+, Glide, and WaterMap)
• Molecular dynamics simulations using e.g. Gromacs, OpenMM and Desmond.
• Ligand analysis using RDKit.
• Python programming, including programming using Schrodinger API
• Machine learning and data analysis
• Markov state modelling
• Teaching and supervision