Scientist, Computational Chemistry
Deep Origin13 days ago
Highlight
OnsiteFull-timeMid
Summary
Deep Origin is seeking a Scientist, Computational Chemistry to join their team in Washington, DC. The role involves leading the design of robust simulation workflows and analyzing protein-ligand structures to support predictive modeling for therapeutic discovery.
About the Role
As a Scientist in Computational Chemistry, you will support a transformative ARPA-H initiative by utilizing your expertise in small-molecule docking, molecular dynamics simulations, and machine learning. Your responsibilities will include analyzing protein targets, running simulations, applying advanced sampling strategies, and collaborating with machine learning and experimental teams to integrate insights across discovery pipelines.
About You
Required:
- Ph.D. in computational chemistry, structural biology, biophysics, or related field.
- 2+ years of postdoctoral or industry experience in structure-based modeling.
- Hands-on expertise with free energy perturbation (FEP) methods.
- Proficiency with simulation platforms such as OpenFE, GROMACS, AMBER, or NAMD.
- Experience with cheminformatics tools like RDKit and machine learning methods for molecular property modeling.
- Strong understanding of protein-ligand binding and conformational variability.
- Programming experience in Python.
Preferred:
- Experience benchmarking across multiple PDB entries or conformational states.
- Prior work integrating structural modeling into machine learning pipelines.
- Familiarity with MM/GBSA, docking scoring functions, or clustering methods.
- Experience using Unix-based HPC environments and workload managers.
- Comfort managing large-scale simulation data.
Benefits
- Opportunity to shape the future of structure-based modeling for therapeutics.
- Work in a collaborative environment at the interface of biology, chemistry, and AI.
Deep Origin
We help scientists solve disease, develop drugs, and extend healthspan by building tools that simplify R&D, simulate biology, and untangle the complexity of life. Streamline computational analysis today. Discover drugs tomorrow.
Washington, DC