We're building the computational tools PPI drug discovery teams have always needed. Join us in Baltimore.
Lead PPI-focused virtual screening campaigns using the Genolux platform. Design and evaluate fragment libraries for interface complementarity. Collaborate directly with oncology biology to prioritize and validate top-ranked hits. PhD in computational chemistry, medicinal chemistry, or related field required; 3+ years post-PhD experience in drug discovery computation.
Build and maintain the Genolux computational pipeline: structure processing, interface characterization, scoring engine, and API layer. Strong Python and scientific Python stack (NumPy, SciPy, RDKit, MDAnalysis) required. Experience with Rosetta, OpenMM, or GROMACS a plus. Excited by scientific software at the research/engineering boundary.
Experimental and computational postdoctoral researcher to develop and validate PPI interface characterization methods. Lead hot-spot mapping and benchmarking projects. Collaborate on manuscript preparation. PhD in structural biology, biophysics, or bioinformatics. Strong background in protein structure analysis and interest in drug discovery applications.
Email [email protected] with the subject line including the role title. Include a brief statement of why you're interested in PPI drug discovery computation, your CV, and links to any relevant publications or code.
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