Ph.D. degree in a scientific field, preferably Chemistry, Biology, Chemical/Biomedical engineering, biochemistry, physics, applied mathematics, bioinformatics, scientific computing or related field.
Experience developing or applying small molecule or protein modeling techniques such as docking, molecular dynamics, free energy perturbation, pharmacophore modeling, quantitative structure activity relationships.
Knowledge of pharmaceutical drug discovery or development. Aware of, but not constrained by today’s approaches.
Inquisitive, creative and bold. Disruptive and innovative thinker that can deliver results.
Excellent written and oral communication skills and the ability to interact effectively outside of the individual’s discipline.
An ability to work and thrive in an extremely energetic, intellectual, fast-paced and matrix environment. Excellent interpersonal abilities, demonstrated inclusivity, flexibility and a history of working collaboratively in a team environment.
Comfortable with risk, willing to fail, learn from it, and move on.
High learning agility and a willingness to contribute at all levels of the ATOM group, including areas outside of the individual’s expertise.
Familiarity with the application of molecular modeling or data-driven modeling techniques in the pharmaceutical industry, and an ability to imagine how these methods could be applied to entirely drive a discovery effort.
An understanding of drug delivery, absorption, distribution and metabolism, pharmacology and toxicology.
Familiarity with deep learning methods, molecular docking and dynamics, and/or free-energy perturbation techniques.
Experience at building, solving and using mathematical models to integrate available data and applying these to answer practical questions and have a positive impact on projects.
Knowledge of the pharma industry and/or the development of human therapeutics.
GSK recently declared its intention to create the Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium with the National Cancer Institute (NCI) and the U.S Department of Energy (DOE). This consortium aims to dramatically accelerate the discovery and development of drugs with an aspiration to go from target to first in human precision trials in twelve months or less. GSK, NCI, and DOE hope to achieve this goal by applying high performance computing modeling and simulation to large datasets that include information about structure and properties of existing and potential drug compounds. As part of GSK’s commitment to this initiative, the company has created several post-doctoral opportunities to work alongside industry and government scientists and be placed at the ATOM facility in San Francisco, CA.
One of these postdoctoral positions will be for a Computational Chemist or Scientist with experience in data-driven, structure-based or mechanistic computational modeling techniques to identify and optimize small molecule drug candidates. The incumbent will be part of a larger cross-functional consortium team at the ATOM facility that will be responsible for developing and employing computational approaches that will significantly accelerate the identification and optimization of small molecule leads in silico.
This is an exciting opportunity to participate in an ambitious collaboration that will integrate high-performance computing, diverse biological data, and new approaches to molecular discovery in an exciting and energetic facility in the heart of San Francisco. Ultimately, the enablement of precision and accelerated discovery of therapeutics will expedite our ability to discover and develop novel medicines that will help patients do more, feel better and live longer.
Participate in the development of overall computational strategies for accelerating the discovery and development of targeted therapeutics for Oncology with a high probability of success.
Build and employ structure-based and data-driven modeling workflows that will facilitate that rapid identification and optimization of in silico-derived leads.
Work with the scientists throughout the ATOM facility to continuously optimize the Discovery process for generating therapeutics with a high probability of success in the shortest amount of time.
Develop mechanisms to share models and data throughout the organization during project execution and archive when appropriate.
Promote and increase the reputation of structure-based and data-driven modeling at the ATOM facility, at partner home organizations, and other external organizations such as regulatory agencies.
Help ATOM eliminate the use of animal models and promote accelerated filing timelines.
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