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Principal Scientist

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GSK

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Location:
United States , Collegeville, Pennsylvania

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Category:
Research and Development

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Contract Type:
Not provided

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Salary:

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Job Description:

The Data, Automation, and Predictive Sciences (DAPS) organization within Research and Development Technologies at GSK works to harness the power of GSK’s data-as-an-asset to drive research productivity. The Cheminformatics (CIX) group is focused on capitalizing on our chemistry and biology data resources to develop, integrate and embed advanced computational methods and predictive in silico models that accelerate the discovery of medicines. As a member of the CIX team, you will be instrumental in marshaling internal datasets and delivering machine learning models built on the strength of those datasets alongside CIX colleagues and business partners to be deployed within the framework of GSK’s small molecule discovery platform.

Job Responsibility:

  • Collaborate with our business partners to engineer pipelines that process elements of GSK’s large proprietary datasets and land model-ready data in the hands of the CIX team
  • Adapt and apply machine learning, active learning, and advanced cheminformatics tools at scale to build robust predictive models for use on drug-discovery programs
  • Contribute to and validate code implementing state-of the-art, production quality methods that accelerate, automate and improve decision making on drug discovery programs by integrating with agentic workflows
  • Prepare and present results of key validation experiments, details of capability builds, and developments on active drug discovery projects to internal and external groups in a way that is both informative and accessible to the non-subject matter expert
  • Work with others within a multidisciplinary matrix team that spans different organizations and geographies to execute on joint objectives

Requirements:

  • PhD or MSc in Cheminformatics, Computational Chemistry, Informatics, Life Sciences, Mathematics or equivalent
  • Experience in computational sciences including knowledge of machine learning, virtual screening, and cheminformatics methods applied to drug design across different modalities
  • Experience programmatically collecting, combining, mining and analyzing complex biological and chemical data to build predictive models, and deploying these methods as pipelines
  • Experience utilizing computer programming and scripting languages such as Python, Java, C/C++, or R with knowledge of basic software development practices
  • Experience with chemical toolkits such as ChemAxon or RDKit and scientific pipelining tools such as Pipeline Pilot or KNIME

Nice to have:

  • Experience applying DNNs to drug discovery-related tasks, such as de-novo molecular generation, reaction and retrosynthetic prediction, or property prediction
  • Experience applying modern experimental design and acquisition strategies to library design and high throughput chemistry including methods such as Bayesian optimization
  • Experience utilizing software development tooling such as GitHub, Azure DevOps, automation and containerization
  • Experience applying cheminformatics & predictive modelling methods in project support scenarios
  • Experience working alongside or within Cloud engineering teams, and deploying agents and LLMs at scale
  • Evidence of strong critical thinking skills, problem-solving & high learning agility
What we offer:
  • Competitive base salary
  • Annual bonus based on company performance
  • Flexible working options available for most roles
  • Learning and career development
  • Access to healthcare & wellbeing programmes
  • Employee recognition programmes
  • Pension plan membership
  • Shares and savings program

Additional Information:

Job Posted:
March 27, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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