Structural Biologist - PhD

Job Description

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

Key Responsibilities

• Analyze protein-ligand interactions to inform medicinal chemistry and leadoptimization efforts.
• Conduct molecular dynamics (MD) simulations and free energy calculations toevaluate 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 orcompound 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 interactionmapping.
• Hands-on experience with molecular dynamics simulations using tools such asGROMACS, 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 andstructural data analysis.

Preferred Qualifications

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

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.