Site Name: USA - Pennsylvania - Philadelphia, USA - North Carolina - Durham
Posted Date: Jan 20 2022
A new position has become available within our Encoded Library Technologies group at GSK, based from our R&D site at Cambridge, MA.
This role will be a part of a new effort to leverage large scale DNA Encoded Library data to address significant challenges in the pre-commit to target through candidate selection. This will require demonstrated data science contributions from inception to delivery and preferably a working knowledge of biology and chemistry within a life science research setting.
The Encoded Library Technologies (ELT*) group at GSK operates at leading edge of drug discovery where at any given point we are seeking affinity probs or starting points for medicinal chemistry for dozens of projects across the entire research portfolio. With over 15 years of production operation we have amassed a quality annotated and orthogonally validated DNA Encoded Library : drug target database with millions of binding measures across hundreds of therapeutically relevant targets. This dataset is integrated as part of the R&D wide assay domain and is accessible by a state of the art global HPC infrastructure totaling over 20 PFlops of compute capability, 20 PB of storage including NVIDIA DGX-2, DGX-3 as well as custom ASIC systems optimized for AI. This role will be a key contributor to the team that scopes, builds, embeds and supports prediction systems that contribute to effective decision making and reduce cycle times.
Key Responsibilities include, but are not limited to:
Accountable for scoping and building predictive analytics systems that maximize impact for Encoded Library Technology data
Contribute to documentation and training materials as part of full lifecycle management to ensure embedding in the scientific organization
Contribute to research of new methodologies as they apply to Encoded Library Technology and/or small molecule discovery associated data
Present and/or write reports on the scientific aspects of the predictive systems for internal and external audiences.
We are looking for professionals with these required skills to achieve our goals:
BS/MS in Data Science/Computational Biology/Chemistry
Demonstrated success in contributing to the delivery of full lifecycle analytics solutions in Biopharma or large academic collaborative efforts in a life science field
Demonstrated e xperience in the creation, execution and interpretation of predictive systems that leverages of at least one of the following for regression or classification: Neural networks, SVM, Gradient Boosting or Random Forest
Experience p rogramming proficiencin Python
If you have the following characteristics, it would be a plus:
Track record of publication in relevant scientific journals and/or invited speaker presentations
Working knowledge of biology and chemistry
Experience working in a matrix environment with input from life scientists, tech, data and AI/ML engineering
Proficiency with deep learning frameworks such as Tensorflow or Pytorch
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