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Research Scientist
2 months ago
We are seeking a highly skilled Research Scientist to join our Cheminformatics team at GlaxoSmithKline. As a key member of our team, you will be responsible for developing and integrating advanced computational methods and predictive models to accelerate the discovery of medicines.
Key Responsibilities- Apply machine learning and related methods at scale to our large proprietary datasets to build robust predictive models for application to drug discovery programs.
- Integrate with program teams to solve drug discovery project issues using cheminformatics tools, platforms, and solutions.
- Contribute to and validate code implementing state-of-the-art, production-quality cheminformatics and computational chemistry methods that accelerate, automate, and improve decision making on drug discovery programs.
- 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.
- PhD or MSc in Cheminformatics, Computational Chemistry, Informatics, Life Sciences, Mathematics, or equivalent.
- Experience in computational sciences, including knowledge of machine learning, computational chemistry, 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.
- Experience developing and utilizing computer programming and scripting languages such as Python, Java, C/C++, R, with knowledge of basic software development practices.
- Experience with chemical toolkits such as ChemAxon, RDKit, and scientific pipelining tools such as Pipeline Pilot or KNIME.
- Experience applying DNN to drug discovery, including de-novo molecular generation, reaction, and retrosynthetic prediction, property prediction.
- Experience working with 3D protein-ligand methods, including structure-based design, virtual screening, molecular docking, molecular dynamics, free energy perturbation.
- 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 across HPC and Cloud, including GitHub, DevOps automation, and containerization.
- Experience applying cheminformatics and predictive modeling methods to project support.
- Evidence of strong critical thinking skills, problem-solving, and high learning agility.
