Research Scientist I, Computational Chemist at Vertex in San Diego, CA

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Job Description:

We are seeking a highly motivated computational chemist to join Vertex's research site in San Diego, California. You will apply computational methods, including structure- and ligand-based drug design, high-throughput virtual screening, molecular dynamics, QSAR models and machine learning techniques to address challenging problems in drug discovery with a focus on designing and optimizing individual molecules and libraries for specific protein targets. Your primary goal will be to advance Vertex' drug discovery projects and actively contribute to our global organization.

Key Responsibilities:
  • Advance structure- or ligand-based drug discovery by introducing computational chemistry methodologies to effectively utilize structural information, molecular modeling techniques, in silico prediction models, chemical library design and data mining.
  • Effectively collaborate with medicinal chemists and structural biologists by providing guidance and support in areas of drug discovery, molecular modeling and informatics.
  • Develop strategies to enhance drug design capabilities, identify quality chemical leads for new protein targets and develop high quality candidates for clinical development.
  • Regularly present research to colleagues in project teams and Computational Chemistry.


Minimum Qualifications:
  • PhD in Computational Chemistry, Medicinal Chemistry, Structural Biology or related discipline
  • 2 years of relevant experience in drug discovery
  • Demonstrated strong track record of research accomplishment in computational chemistry, medicinal chemistry or structural biology with three or more scientific publications or conference presentations.
  • Solid understanding of medicinal chemistry as it applies to hit finding and lead optimization. Understanding of molecular and ADMET properties and protein-ligand interactions and experience using an integrated molecular modeling software platform to perform docking, conformational analysis, pharmacophore derivation, shape overlay, and quantum-mechanics calculations.
  • Effective communication skills and enthusiasm for working in interdisciplinary teams that include medicinal chemists, biologists, structural biologists and scientists from DMPK.
Preferred Qualifications:
  • Ability to interpret and communicate structural information to medicinal chemists, and proactively suggest ideas for potency, selectivity and ADMET improvements within the design cycle.
  • Highly desire familiarity with Machine Learning techniques, Statistics, Multiple Parameter Optimization methods, Molecular Dynamics, Bioinformatics and homology modeling approaches as well as experience with scripting or programming languages like Python.

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