Job Description

For 14 years, Nimbus Therapeutics has placed structure-based drug design and computational chemistry in a central role in its mission to develop breakthrough medicines, and has successfully delivered multiple class-leading drug candidates to the clinic.  As Nimbus enters a new chapter, we are redoubling this commitment and seeking an exceptional Computational Chemist to join our team.  This position offers an exciting opportunity to work within an experienced, cross-disciplinary team savvy with computational strategies to drive the development of future drug candidates and to actively partner within the computational chemistry team on joint objectives to remain cutting-edge in computational drug discovery. The successful candidate will be an expert in aspects of computational chemistry, experienced in structure-based molecular design informed with both physics- and AI/ML-based computation, and will be passionate about drug discovery.  You will report to our Head of Computational Chemistry.

In this role, you will:

• Be tightly integrated in a multidisciplinary drug discovery team making substantial intellectual contributions to program direction, molecular design, and synthetic priority
• Creatively applying physics and chemoinformatics-based methods to solve challenges throughout the lifetime of the discovery process and accelerating the time to drug candidate
• Develop and apply both novel and precedented machine learning methodology to inform programs at all stages of discovery, and in particular to the prediction and optimization of ADMET and physiochemical properties.  This may include developing or coordinating aspects throughout the machine learning lifecycle: implementing new methodology, applying existing methods to new endpoints, data acquisition/curation, and/or automating benchmarking, retraining, and redeployment
• Contribute to the computational chemistry team strategy by identifying novel directions and technologies that complement and expand our structure-based discovery engine
• Contribute to external presence of team, including publishing/presenting critical research
• Collaborate with discovery scientists to maximize savvy usage of predictive modeling

These Qualifications Will Help This Role Be Successful:

• PhD. in computational chemistry, chemistry, chemical engineering, biochemistry, biophysics, or a related scientific field with a computational focus on small molecule chemistry and protein structure.  Applicant should be fluent in chemistry to influence compound design and productively engage with medicinal chemists and other discovery scientists.
• 4+ years industry experience in pharma/biotech, effectively operating in a multidisciplinary drug discovery team environment and successfully impacting discovery. 
• Deep understanding of medicinal/computational chemistry principles of ligand and structure-based design, DMPK principles, and multi-parameter optimization is expected.
• Competency with scientific scripting/programming is highly preferred, as is competence with the Schrödinger suite of software.
• Excitement and understanding of deep learning techniques that are emerging in the chemistry domain, including knowledge of the landscape of public code repositories and their utility, would be distinguishing.   
• Excellent verbal and written communication with strong publication record and organizational skills required.
• Ability to navigate, problem-solve, execute, and lead in a dynamic, fast-paced and evolving environment.

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