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Job Description
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:
- Solid 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.
- Cooperative and interdisciplinary research workplace.
- Access to state-of-the-art computational and structural biology platforms.
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