Bridging the gap between theoretical chemistry, computational methods, and machine learning applications
I'm a Principal Life Science Innovation Lead at Intellegens.
- PhD in Computational and Theoretical Chemistry
- MPhil in Scientific Computing
- MChem in Pure and Applied Chemistry
- PMF Calculations
- Statistical Mechanics
- Thermodynamics
- Chromatin Dynamics
- Biomolecular Simulation
- Molecular Dynamics
- Enhanced Sampling Techniques
- Machine Learning
- Design of Experiments
- VMD, PyMOL & Ovito for molecular visualization
- Blender for animations
As a Principle Life Science Innovation Lead, I specialize in:
- Developing ML models for chemical and life sciences applications
- Creating predictive models for specific applications such as pharmacokinetic properties, QSAR and optimising chemical synthesis.
- Bridging scientific domain knowledge with advanced ML techniques
I'm currently working on several exciting projects that combine my interests in computational chemistry, machine learning, and software development:
- Oligonucleotide ML Development - Developing machine learning models for oligonucleotide analysis and prediction
- Website Design - Personal site
- Learning Rust - Exploring Rust for scientific computing
- Bioanalysis Library - Creating a comprehensive library for bioanalytical data processing and analysis
I'm always open to interesting scientific collaborations and discussions on personal projects:
