Computational ADMET Scientist - Drug Metabolism/Metabolomics Focus

Summary

Join Deep Origin, a biotechnology company leveraging AI in drug discovery, as a Computational ADMET Scientist. Design and build predictive systems for Phase I and Phase II metabolic pathways, directly contributing to AI-driven tools that predict metabolic routes, enzyme involvement, and metabolite toxicity. This role requires a creative scientist skilled in data mining, statistical and kinetic modeling, cheminformatics, machine learning, and computational chemistry. You will develop and refine computational approaches, build algorithms, predict enzymes, assess metabolite toxicity, and integrate diverse datasets. Collaboration with a cross-functional team and documentation of methods are key aspects of this position. The ideal candidate will thrive in a fast-paced, deadline-driven environment and possess a strong work ethic.

Requirements

• PhD (0-2 years) or MS (2-5 years) of relevant experience in Bioinformatics, Systems Biology, Computational Chemistry, or related field
• Strong coding skills in Python (additional languages a plus)
• Proven expertise in drug metabolism, with demonstrable experience in metabolism prediction
• Hands-on experience with cheminformatics and ML libraries such as RDKit, CDK, PyTorch, TensorFlow
• Ability to critically analyze data and translate findings into actionable predictions and computational models
• Collaborative mindset, comfortable working in both autonomous and team-based settings
• Adaptability to thrive in a fast-paced, deadline-driven environment

Responsibilities

• Develop and refine computational approaches to predict Phase I and Phase II metabolic transformations with high sensitivity and precision
• Build and optimize algorithms to identify sites of metabolism and predict regioselectivity
• Predict enzymes and related isoforms responsible for a given chemotype
• Assess toxicological profiles of metabolites
• Integrate diverse datasets (experimental and computational) for improved prediction accuracy
• Collaborate across a cross-functional scientific team
• Document methods and contribute to technology commercialization
• Contribute novel ideas to the team
• Show a high work ethic within the autonomous remote framework

Preferred Qualifications

• Familiarity with PBPK (Physiologically-Based Pharmacokinetic) modeling
• Prior pharmaceutical or biotech industry experience

Benefits

• Work on impactful problems at the frontier of AI + chemistry + biology
• Collaborate with multidisciplinary teams of scientists
• Shape next-generation tools for predictive drug discovery