Job Description

• We are seeking a highly skilled and motivated Structural Biologist to join our drug discovery programs. The ideal candidate will bring deep expertise in macromolecular structure determination and modeling, with a focus on elucidating protein structures, analyzing ligand binding, and driving rational drug design in collaboration with computational and medicinal chemistry teams.

Key Responsibilities

• Analyze protein-ligand interactions to inform medicinal chemistry and lead optimization efforts.
• Conduct molecular dynamics (MD) simulations and free energy calculations to evaluate complex stability and binding energetics.
• Apply structural insights to guide hit-to-lead and lead optimization strategies.
• (Preferred) Utilize machine learning models to support binding site prediction or compound prioritization.

Required Skills & Experience:

• Strong expertise in structural biology techniques, such as crystallography, cryo- EM, or NMR are desirable.
• Proficient in macromolecular modeling and structure refinement tools (e.g., Phenix, Coot, Chimera, PyMOL).
• Experience with protein-ligand docking, structure validation, and interaction mapping.
• Hands-on experience with molecular dynamics simulations using tools such as GROMACS, AMBER, NAMD, or CHARMM.
• Familiarity with structure-based drug design platforms (e.g., Schrödinger, AutoDock).
• Scripting or programming experience (Python, R, Bash) for workflow automation and structural data analysis.

Preferred Qualifications

• Ph.D. in Structural Biology, Biophysics, Computational Biology or related field.
• Demonstrated experience in drug discovery pipelines, especially in target validation and lead optimization.
• (Preferred) Background in machine learning or AI applied to biomolecular structure or ligand interaction prediction.
• Strong publication record or demonstrated project impact in therapeutic development.

What We Offer

• Work on high-impact, discovery-stage therapeutic programs.
• Collaborative and interdisciplinary research environment.
• Access to state-of-the-art computational and structural biology platforms.