Scientist / Senior Scientist, Structure-Based Modeling

Scientist / Senior Scientist, Structure-Based Modeling

Portugal

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
- 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
- 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
  - 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+, Open
  MM, GROMACS, AMBER, NAMD);
• Strong understanding of
  - ligand binding, structure selection, and conformational variability;
• Programming experience in Python, and familiarity with tools like MDAnalysis, Py
  MOL 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
  - scale simulation data for modeling or analysis
  
  

Responsibilities:

• Analyze tens to hundreds of protein targets relevant to ADMET and
  - targets, focusing on conformations, binding site flexibility, and
  - bound states to guide structure preparation and ensemble design;
• Run and refine docking, MD, and FEP (RBFE and ABFE) simulations using
  -
  -
  - art tools;
• Apply methods such as restraints, alchemical transformations, and sampling strategies to ensure robust and reproducible FEP workflows;
• Curate, benchmark, and select optimal
  - 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
  - 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
- based modeling for therapeutics.

We offer:

• A
  - first team across the US, Europe, and Armenia;
• Competitive salary and equity packages;
• Flexible working hours;
• A
  - 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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