Director, AI Discovery

Role Summary

The Director will lead the strategic development and application of artificial intelligence (AI) and computer-aided drug design (CADD) to accelerate research and development at Tonix. This role will drive innovation across both small- and large-molecule programs by integrating ligand- and structure-based design with AI/ML to identify and optimize novel therapeutic candidates. The Director will collaborate with chemists, biologists, data scientists, and software engineers to develop data-driven strategies to advance Tonix's pipeline on CNS, rare disease, immunology, and infectious disease. The position will also help build scalable AI infrastructure to support informed decision-making across Tonix's discovery portfolio. The Director will ensure that AI and computational initiatives align with Tonix's organizational goals and research priorities, delivering impactful results that support both preclinical research and long-term development objectives.

Responsibilities

• Define and implement Tonix's computational and AI-driven drug discovery strategy in alignment with company R&D priorities.
• Lead computational and AI-enabled design initiatives to accelerate drug discovery and development.
• Develop and apply AI/CADD-based approaches to target validation, hit-to-lead optimization, ADME/Tox profiling, and preclinical safety and efficacy assessment.
• Develop and integrate scalable AI/ML tools, data workflows, and high-performance computing solutions to support Tonix's discovery pipeline.
• Collaborate closely with chemists, biologists, pharmacologists, and informatics experts to translate computational insights into actionable experimental hypotheses.
• Contribute to publications, patents, and presentations that enhance Tonix's scientific visibility in AI-enabled drug discovery.

Qualifications

• Ph.D. in Pharmacology, Chemistry, Structural Biology, or a related discipline.
• 20 years of experience in drug design and discovery, including leadership in developing and applying AI/CADD approaches to advance programs from concept to clinical stage.
• Ligand-based drug design expertise: AI/ML, QSAR, neural networks, pharmacophore modeling, de novo design, virtual screening, and ADME/Tox modeling.
• Structure-based drug design expertise: sequence analysis, protein modeling, molecular docking, AlphaFold, molecular dynamics simulations, and free energy perturbation.
• Proficiency with modern molecular modeling platforms, such as Schrödinger, MOE, AlphaFold, and AMBER.
• Experienced in AI/ML programming and data analysis, such as Python (Jupyter Notebook, Chemprop, RDKit, Scikit-learn, NumPy, Pandas) and bash scripting.
• Strong understanding of CNS, pain biology, and translational pharmacology.
• Demonstrated ability to collaborate effectively in multidisciplinary settings and to communicate complex modeling results to non-specialist teams.
• Experience managing collaborations with external chemistry partners and CROs.
• Proven leadership, project management, and mentorship capabilities.