Scientist​/Senior Scientist, Structure- Modeling

Scientist / Senior Scientist, Structure-Based Modeling Scientist / Senior Scientist, Structure-Based Modeling

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Deep Origin is seeking a Scientist or Senior Scientist with strong expertise in structure-based drug design, including docking, molecular dynamics (MD), and free energy perturbation (FEP), to support a transformative ARPA-H initiative. You'll lead the design of robust simulation workflows and analyze protein-ligand structures across a large target panel to support predictive modeling for therapeutic discovery.

Requirements

• 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 FEP (RBFE/ABFE), including best practices around setup, sampling, and analysis;
• Proficiency with one or more simulation platforms (e.g., Schrödinger FEP+, OpenMM, GROMACS, AMBER, NAMD);
• Strong understanding of protein-ligand binding, structure selection, and conformational variability;
• Programming experience in Python, and familiarity with tools like MD Analysis, PyMOL APIs, or MDTraj;
• Fluent English for collaboration with an international team;
• Ability to work on US time zones when needed

Nice to have:

• 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, workload managers (e.g., SLURM, etc.), and optionally AWS;
• Comfort managing large-scale simulation data for modeling or analysis

Responsibilities:

• Analyze tens to hundreds of protein targets relevant to ADMET and off-targets, focusing on conformations, binding site flexibility, and ligand-bound states to guide structure preparation and ensemble design;
• Run and refine docking, MD, and FEP (RBFE and ABFE) simulations using state-of-the-art tools;
• Apply methods such as restraints, alchemical transformations, and sampling strategies to ensure robust and reproducible FEP workflows;
• Curate, benchmark, and select optimal protein-ligand structures (e.g., from PDB) for predictive modeling;
• Evaluate multiple structural representations (e.g., different PDB IDs) to determine the best input per target;
• Collaborate with cheminformatics, ML, and experimental teams to integrate structure-based insights across discovery pipelines;
• Communicate progress, technical findings, and challenges across internal and external teams

Why Join Deep Origin

Deep Origin builds modern infrastructure for computational science at the interface of biology, chemistry, and AI. As part of our ARPA-H program, you'll shape the future of structure-based modeling for therapeutics.

We offer:

• A remote-first team across the US, Europe, and Armenia;
• Competitive salary and equity packages;
• Flexible working hours;
• A mission-driven, scientifically rigorous culture that values autonomy and impact

Seniority level

• Seniority level
  
  Mid-Senior level

Employment type

• Employment type
  
  Full-time

Job function

• Job function Other
• Industries
  
  IT Services and IT Consulting

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