Computational Toxicologist (Comp. Toxicologist)(J24819)

Role overview Predict drug safety issues in silico and filter out toxic scaffolds before a single molecule is synthesized. We are seeking a pragmatic, delivery oriented Computational Toxicologist to join our integrated discovery team in Shanghai. You will embed in early discovery workflows to identify safety liabilities, advise on design risk mitigation, and produce regulatory grade in silico safety assessments that accelerate go/no go decisions for global biotech clients. Key responsibilities • Perform comprehensive in silico toxicology assessments across discovery portfolios: genotoxicity, hERG, hepatotoxicity, reactive metabolites, and other safety pharmacology endpoints. • Integrate QSAR tools, expert rule based systems and toxicogenomics data to prioritize or de prioritize AI proposed chemotypes before synthesis. • Run and interpret DEREK, MultiCASE, Leadscope and other predictive toxicology platforms; build and validate QSAR models where needed. • Apply ICH M7 and other relevant regulatory frameworks to classify mutagenic risk and recommend appropriate mitigation strategies. • Generate clear, defensible safety reports and data packages for client decision making and for inclusion in regulatory submissions (e.g., INDs). • Collaborate closely with computational chemists, medicinal/synthetic chemists, DMPK and biology teams to translate safety findings into actionable design constraints and SAR strategies. • Contribute to client presentations, proposal writing and bid defense by articulating safety risk, recommended assays and mitigation paths. • Maintain reproducible workflows and documentation for model inputs/outputs, and implement best practices for data management and version control. • Mentor junior tox scientists and help scale the in silico safety practice across the company.

• Ph.D. or M.S. in Toxicology, Pharmacology, Computational Biology, Cheminformatics or a closely related discipline. • 5+ years’ industry experiences predicting safety liabilities in drug discovery (Big Pharma or preclinical CROs preferred). • Hands on experience with DEREK, MultiCASE, Leadscope and QSAR toxicity models; comfortable developing and validating predictive models. • Deep working knowledge of safety endpoints: genotoxicity, hERG, hepatotoxicity, reactive metabolites, off target liabilities and safety pharmacology. • Practical understanding of ICH M7 and other regulatory guidance relevant to in silico assessments. • Strong communication skills with the ability to present complex safety data to cross functional teams and external clients. • Excellent documentation skills and familiarity with delivering regulatory grade assessments. Preferred / Nice to have • Direct experience contributing to in silico safety sections of IND or other regulatory submissions. • Prior experience in Safety Pharmacology or Preclinical Toxicology groups within Big Pharma or large preclinical CROs. • Experience integrating toxicogenomics or transcriptomics data into predictive safety assessments. • Publications or presentations in computational toxicology, QSAR or regulatory toxicology. • Familiarity with coding/scripting (Python, R) for data processing and model automation. What we offer • The chance to prevent costly downstream attrition by catching safety liabilities early — work at the interface of AI, chemistry and safety science for global clients. • Cross functional teams with tight integration between computational design, synthetic chemistry, DMPK and biology for rapid feedback loops. • Competitive compensation and benefits aligned with market and experience. • Career growth through technical leadership, regulatory participation and client engagement opportunities. How to apply Please submit your CV and a brief cover note that includes: • One or two case studies where your in silico assessments influenced project decisions (describe your role, tools used, and outcomes). • Any contributions to regulatory filings or relevant publications. Shortlisted candidates will be invited to present a recent in silico safety assessment, explain model selection/validation, and discuss how recommendations were implemented in discovery. We welcome applicants based in Shanghai or those willing to relocate.