Worked at the interface of the AI and biotech teams on structure-based drug discovery, generative molecular design, and applied machine learning — the link between the computational tools and the biology.

• Contributing author on a NeurIPS 2025 paper on uncertainty quantification for deep regression: ran the empirical validation and fine-tuned/retrained models in PyTorch
• Built a modular synthetic-data-generation pipeline (Python, Biopython) orchestrating GNINA, DiffDock and AlphaFold 2, including dataset sourcing and inter-tool format conversion
• Predicted structures and binding affinities for protein and protein–peptide complexes, including metal-ion and ATP cofactors, and designed de novo peptides, using Boltz, BoltzGen, AlphaFold, Foldseek and BioEMU
• Developed the binding-affinity objective for the multi-objective small-molecule optimisation engine of Uncharted, a venture that spun out as Uncharted Chem
• Applied AI tools and data analysis to cancer-research and gut-microbiota (metagenomic) programmes; prototyped a novel operon-design approach for extremophile bacteria and ran statistical power analyses for preclinical studies
• Ran GPU workloads on an NVIDIA DGX cluster and AWS; Docker, Git and Azure DevOps within an Agile/Scrum team

Quantitative sensory biology within an international Human Frontier Science Program (HFSP) collaboration, with emphasis on statistical modelling and signal processing of behavioural data.

• Analysed experimental data using Bayesian multilevel regression models in R and Stan
• Designed and executed behavioural experiments with automated data acquisition pipelines
• Contributed to interdisciplinary publications spanning biology, optics, and computation

Computational and statistical analysis of visual systems in invertebrates, combining experimental biology with quantitative modelling.

• Built statistical models using Bayesian multilevel regression in R and Stan; additional analysis in Python and Matlab
• Developed optical and geometric models to estimate spatial resolution theoretically
• Designed novel experimental protocols for quantifying animal visual performance