Principal Scientist to Associate Director, CADD

Job description

About Us: Structure Therapeutics develops life‐changing medicines for patients using advanced structure‐based and computational drug discovery technology. The company’s platform combines the latest advancements in visualization of molecular interactions, computational chemistry, and data integration to design orally available, superior small molecule medicines that overcome current limitations of biologic and peptide drugs. We are advancing a clinical‐stage pipeline of differentiated treatments focused on chronic diseases with high unmet need, including cardiovascular, metabolic, and pulmonary conditions. Structure Therapeutics is led by an experienced group of international drug innovators and financed by top-tier global life sciences investors. The company completed an initial public offering (IPO) in February 2023. With offices in California and Shanghai, Structure Therapeutics has the benefit of being at the center of life science innovation in both the US and China and capitalizing on the strengths of each geographic location. Position Summary We are seeking a talent in Computational Chemistry (CADD) to play a key hands-on role in small-molecule design and optimization. This individual will apply state-of-the-art molecular dynamics (MD), structure-based methodologies, and cheminformatics tools to drive discovery programs. The ideal candidate will have strong problem-solving skills and the ability to collaborate closely with medicinal chemists, structural biologists, and biologists. This role provides an exciting opportunity to directly influence hit identification, hit-to-lead progression, and lead optimization for first-in-class and best-in-class therapeutics. Job Responsibilities: Apply molecular dynamics (MD) simulations to evaluate protein–ligand interactions, conformational states, binding mechanisms, and design hypotheses. Support structure-based drug design through docking, pharmacophore modeling, QM/DFT calculations, and physics-based scoring. Perform virtual screening, scaffold hopping, and hit identification using both ligand-based and receptor-based approaches. Analyze SAR, ADME trends, and structural data to propose new analogs and guide medicinal chemistry optimization. Develop or implement computational workflows for potency, selectivity, and physicochemical property predictions. Build or apply machine learning models (if applicable) to support predictive design. Communicate results, insights, and design proposals clearly across multidisciplinary project teams. For Principle Scientist and above: help influence project strategy and technical direction. Qualifications: The ideal candidate will bring: Ph.D. in computational chemistry or a related field, plus industry experience. Essential: Strong capability and hands-on experience in molecular dynamics (MD) simulations (e.g., GROMACS, AMBER, CHARMM, NAMD, Desmond) and FEP (Free Energy Perturbation). Strong experience in structure-based drug design and molecular modeling. Proficiency with computational chemistry software such as Schrödinger Suite, OpenEye, Rosetta, Spotfire, etc. Experience with machine learning or co-folding tools is a plus. Experience with GPCRs or other membrane protein targets is a plus. Python or similar scripting skills for workflow automation or data analysis is desirable. Strong communication skills and ability to work effectively in cross-functional teams. Scientific creativity, attention to detail, and a track record of problem-solving. Publications and/or patents demonstrating scientific achievements.