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OpenEye, Cadence Molecular Sciences – a division of Cadence Design Systems – is an industry leader in computational molecular design through rapid, robust, and scalable software, consulting services, and Orion®, the only cloud-native fully integrated software-as-a-service molecular modeling platform. Combining unlimited computation and storage with powerful tools for data sharing, visualization and analysis in a customizable development platform, Orion offers unprecedented capabilities for the advancement of pharmaceuticals, biologics, agrochemicals, and flavors and fragrances. OpenEye, Cadence Molecular Sciences is headquartered in Santa Fe, N.M., with offices in Boston, Mass.; Cologne, Germany; and Tokyo, Japan

This internship opportunity focuses on advancing computational approaches for understanding how cryptic pockets influence protein function through allosteric effects. You will help develop and validate an algorithmic framework for predicting how the effect of binding at detected pockets propagates through the entire protein structure, enabling users to identify which pockets are most likely to impact key functional regions. This internship offers hands-on experience with developing and validating computational methods on well-characterized protein targets with known allosteric sites, which will later be integrated into a larger workflow for connecting cryptic-pocket detection to functional interpretation of the ligand binding.

Key Learnings:

You have the opportunity to improve problem-solving skills in a professional scientific setting. Work on well-established protein systems with cutting edge scientific methods and cloud based computing technology. Develop software engineering capabilities in a professional environment through following established coding standards, testing practices, and version-control workflows to produce robust, maintainable, and well-documented code. Practice communication and presentation abilities. Present progress update and key findings to a group of proficient scientists and developers in a clear, structured manner.

What you should have:

• Extensive programming experience.
• Current graduate students or advanced undergraduate students in computational biology, chemistry, biophysics, or related fields are preferred.
• Strong scientific skills in problem-solving, protein structure analysis, and presenting key findings.

The following are a PLUS, but not required:

-Proficiency in Python.

-Familiarity with normal mode analysis.

-Solid understanding of linear algebra.

-Basic knowledge of linear response theory and/or the perturbation-response scanning method.

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