Associate Director, Computational Chemistry

Jnana Therapeutics, a wholly owned subsidiary of Otsuka Pharmaceutical, is a clinical-stage biotechnology company leveraging its next-generation RAPID chemoproteomics platform to discover medicines for highly validated, challenging-to-drug targets to treat diseases with high unmet needs. Jnana is focused on developing first- and best-in-class therapies to treat a wide range of diseases, including rare diseases and immune-mediated diseases. Jnana’s lead program, JNT-517, which targets an allosteric site on the phenylalanine transporter SLC6A19, is a potential first-in-class oral approach for the treatment of PKU, a rare genetic metabolic disease.

Located in Boston, Jnana brings together scientific leaders in small molecule drug discovery and development, and a highly experienced management team. For more information, please visit  and follow us on Twitter/X and Linked In.

At Jnana, you'll join a diverse, passionate team dedicated to advancing therapies for challenging diseases. Our collaborative, purpose-driven culture fosters innovation, urgency, and belonging—making Jnana a great place to work!

As an Associate Director of Computational Chemistry, you will be integral to our drug discovery efforts, applying structure-based drug design methods to optimize molecules and guide medicinal chemistry strategy through all parts of the discovery process. This position will be working collaboratively in cross-functional teams to deliver models, predictions and actionable insights that accelerate progress toward clinical development.

You will join a team of highly skilled computational scientists eager to drive projects while developing and applying new tools and methods with exceptional scientific rigor. This is an exciting opportunity to join a growing computational chemistry team with the passion, resources and mandate to build a world-class group.

• Act as the computational lead on therapeutic projects, conducting structure-based drug design efforts including molecular dynamics simulations, free energy perturbations, docking and structure analysis to guide medicinal chemistry synthesis priorities.
• Partner closely with medicinal chemists and project leads to interpret structural data, rationalize structure-activity relationships, and propose optimized compound designs that address potency, selectivity, and develop ability objectives.
• Contribute to lead optimization strategy by integrating structural insights with ADME, safety, and physicochemical property considerations to drive molecules toward clinical candidates.
• Communicate findings clearly to project teams and leadership, presenting design recommendations and structural insights that inform decision-making and advance programs.
• Stay current with advances in computational chemistry methods and the drug discovery environment, evaluating and implementing new approaches that enhance capabilities and improve results.

• PhD in Computational Chemistry, Medicinal Chemistry, or a related field with substantial industry experience (6+ years) and demonstrated ownership of cross-functional research projects.
• Demonstrated track record of applying structure-based drug design to successfully advance multiple drug discovery projects through lead optimization stages.
• Experience supporting IND-enabling activities and contributing to regulatory filings.
• Deep expertise in molecular modeling techniques and industry-standard tools for molecular dynamics simulations, free energy calculations, protein-ligand docking, structure analysis, binding mode prediction, and design hypothesis generation from structural data.
• Strong understanding of medicinal chemistry principles, structure-activity relationships, and the interplay between potency, selectivity, ADME properties, and develop ability.
• Experience working with diverse structural biology data including X-ray crystallography and cryo-EM and translating these data into actionable medicinal chemistry recommendations.
• Proven ability to work effectively in fast-paced, collaborative drug discovery teams and communicate complex computational results to non-computational…