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.