Valence Laboratories

Research Scientist

• Research and develop generative and distributional models (e.g., flow matching, diffusion models) to predict high-dimensional cellular responses.
• Build and maintain ML systems capable of processing massive multiomics datasets on high-performance compute clusters.
• Work closely with colleagues to ensure model predictions are interpretable, trustworthy, actionable, and grounded in real experimental outcomes.
• Help design and implement rigorous evaluation metrics that test generalization across for cellular context, unseen perturbations and covariates, going beyond IID performance to reflect real deployment conditions.
• Publish findings in top-tier venues (e.g., NeurIPS, ICML, Nature, Science, Cell) and contribute to the broader scientific community.

Research Scientist, Virtual Cell Modelling, Perturbative Biology