Associate Director, Computational Chemistry

As a leader within our Computational Chemistry team, you will:

• Serve as a computational chemistry lead on multidisciplinary discovery teams, shaping project direction and compound design from hit finding through lead optimization.
• Integrate SAR, structural, biophysical, biochemical, and ADME/PK data to guide prioritization of Ro5 and bRo5 molecules.
• Lead CompChem's contribution to TQ, translating discovery strategy into computational objectives, work plans, and milestones.
• Coordinate execution across TQ efforts and be accountable for the quality, timeliness, and scientific impact of the work.
• Partner with medicinal chemistry, structural biology, biology, and screening leaders to define key scientific questions, resolve complex discovery challenges, and recommend priorities.
• Communicate evidence, uncertainties, and trade-offs to project teams and senior leadership.
• Establish and advance hit-finding strategies for novel protein and protein-protein interaction targets, including structure-based and ligand-based virtual screening and the design of diverse chemical libraries.
• Guide the evaluation, development, and application of computational methods, including molecular dynamics, enhanced sampling, and free energy calculations.
• Remain hands-on in solving challenging modeling and molecular design problems.
• Collaborate with Advanced Analytics to develop, validate, and apply AI/ML methods that address computational chemistry and drug discovery needs.
• Set computational priorities across assigned discovery programs and TQ responsibilities, in alignment with the Head of Computational Chemistry and project leads.
• Identify staffing, compute, software, and external collaboration needs; provide budget and resource recommendations and track delivery against agreed plans.
• Provide scientific leadership and lead cross-functional initiatives.
• Establish standards for reproducibility, model evaluation, and knowledge sharing, and support the adoption of effective methods across discovery teams.
• Have the opportunity to manage and develop junior scientists, supporting their scientific development and contributions to discovery projects.

Required Skills, Experience and Education:

• Ph.D. in computational chemistry or a related field.
• 10+ years experience post PhD.
• Substantial computational chemistry experience in the biotechnology or pharmaceutical industry, with demonstrated scientific leadership across discovery programs and a track record of influencing program strategy, advancing compounds, or enabling key discovery decisions.
• Expert knowledge of computational chemistry methods for protein-ligand analysis and molecular design, including docking, virtual screening, pharmacophore modeling, molecular dynamics, and free energy or quantum mechanical calculations.
• Experience developing, validating, and applying AI/ML or data science approaches to drug discovery, with sound judgment in model evaluation, uncertainty, applicability, and experimental validation.
• Strong scientific programming skills in Python or related languages, and experience with computational chemistry, cheminformatics, and machine learning software.
• Demonstrated ability to set scientific priorities, develop work plans, coordinate resources, and lead scientists or cross-functional programs.
• Ability to influence senior stakeholders and communicate complex findings and recommendations clearly.
• A collaborative leadership style, a record of mentoring scientists, and the ability to balance exploratory research with discovery timelines and deliverables.

Preferred Skills:

• Experience with Ro5 and bRo5 modalities, including macrocycles, molecular glues, tri-complex inhibitors, covalent ligands, or other challenging therapeutic modalities.
• Experience working in HPC or cloud environments and developing scalable computational workflows.
• A record of scientific innovation reflected in patents, publications, presentations, or the adoption of methods that improve discovery outcomes.
• Experience managing direct reports, external scientific collaborations, or budgets.