Computational Biologist

The AI Computational Biologist will develop and apply AI-driven models to support target discovery, mechanism elucidation, and therapeutic hypothesis generation. This role bridges advanced computational modeling with biological insight, working closely with AI engineers and wet-lab scientists to translate in silico findings into preclinical research.

• Design, train, and apply LLM- and GNN-based models using multi-modal biological data, including omics, literature, and clinical datasets
• Integrate knowledge graphs and biomedical databases to generate and prioritize targets and mechanisms
• Interpret computational outputs to support target identification, biomarker discovery, and patient stratification
• Collaborate with wet-lab teams to translate predictions into experimental designs and validation studies
• Curate and integrate large-scale biological datasets to support model development and fine-tuning
• Communicate findings clearly to cross-functional scientific and technical teams

• PhD or MS with 5+ years of relevant experience in computational biology, bioinformatics, systems biology, computer science, or a related field
• Strong background in molecular biology, pharmacology, and disease biology
• Hands-on experience applying AI/ML models to biological problems, particularly LLMs, GNNs, and multi-modal approaches
• Proficiency in Python and common ML frameworks (e.g., PyTorch, Tensor Flow)
• Experience with biological databases and multi-omics data integration