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. 

DAPS and CIX will only be successful by working in close collaboration with these business partners, including other groups within DAPS and Research Technologies, Therapeutic Areas, GSK Tech, AIML, Vaccines, and Risk & Compliance.  We strive to foster and develop a high-performing team culture of collaboration, curiosity, consistency, agility, quality, peer review, and continuous improvement with a relentless focus on enabling value realization through end-user uptake and measuring impact.      

We create a place where people can grow, be their best, be safe, and feel welcome, valued and included. We offer a competitive salary, an annual bonus based on company performance, healthcare and wellbeing programs, pension plan membership, and shares and savings program.

We embrace modern work practices; our Performance with Choice program offers a hybrid working model, empowering you to find the optimal balance between remote and in-office work.  Discover more about our company wide benefits and life at GSK on our webpage Life at GSK | GSK

Key Responsibilities:

This role will provide YOU the opportunity to lead key activities to progress YOUR career, these responsibilities include some of the following.

• 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

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

• 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

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

• 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

#GSK-LI

Please visit  GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

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GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

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