Principal ML Scientist – Predictive Toxicology

📋 Description The Principal ML Scientist will own the expansion of predictive toxicology and quantitative biology Lead the development and execution of the scientific strategy for predictive toxicology Define modelling approaches, biological endpoints, and data strategies that support better safety Build and optimize machine learning models using advanced molecular AI techniques, including graph Apply federated learning approaches to enable collaborative model development across multiple Integrate scientific workflows involving multi-omics, image-based screening, high-throughput 🎯 Requirements PhD or equivalent experience in computational biology, cheminformatics, toxicology, machine 6+ years of experience applying machine learning techniques to drug discovery, computational Strong understanding of deep learning methods for molecular AI and predictive modelling. Proven experience developing predictive toxicity models and supporting their adoption within Knowledge of toxicity assessment workflows, including DILI, cytotoxicity, genotoxicity, or related Experience working with biological datasets such as RNA-seq, toxicity screening data, image-based 🎁 Benefits Competitive compensation package, including virtual share options. Fully remote-first working model with flexibility to work from the location that suits you best. Wellbeing budget and mental health support. Work-from-home budget and co-working stipend. Learning and professional development budget. Generous holiday allowance.