Principal Scientist, Translational Omics Full-time

Computational Biologist

For candidates seeking to be located at our Stevenage site, this role will temporarily be based at Stevenage. However, the Company plans to relocate its offices to [Cambridge, UK] [Ware]. The location of this role will therefore subsequently change to [Cambridge, UK] [Ware] in accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029.

At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people's lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients' needs and have the highest probability of success. We're uniting science, technology, and talent to get ahead of disease together.

We are seeking a motivated computational biologist to focus on analysis and integration of diverse and complex multi-omic data to deliver actionable insights that will help bring the right medicines to the right patients. Your work will have application across our pipeline, from multi-omic characterisation of disease endotypes to biomarker discovery and patient stratification, with a focus on hepatology, renal, metabolic and cardiovascular disease. You will lead and contribute to the analysis and integration of cutting edge high dimensional multi-omic data, including single cell and spatial transcriptomics, proteomics, metabolomics and lipidomics to derive insights that will impact GSK pipeline decisions.

The successful candidate will work in a multidisciplinary, collaborative and scientifically driven environment, interacting with GSK scientists and external collaborators to advance drug discovery and clinical development. Additionally, you will be encouraged and supported to continue to build your scientific profile through presentations, development programmes and peer-reviewed publications.

Key Responsibilities

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

• Impact the GSK drug development pipeline through development and application of innovative computational and statistical approaches to the analysis, integration and interpretation of spatial, single cell and other cutting edge high dimensional multi-omic data.
• Work within cross-functional project teams with GSK scientists and external collaborators, with a focus on impacting target, biomarker and clinical study decisions across hepatology, renal, cardiovascular disease.
• Effectively communicate analysis findings and recommendations, with expert interpretation, to project teams.
• Work with focus and agility to deliver against objectives, demonstrating strong statistical, analytical and critical thinking skills.

Why You? Basic Qualification

We are seeking professionals with the following required skills and qualifications to help us achieve our goals:

• PhD or master's degree with 10+ years' experience in computational biology, bioinformatics, computational sciences or machine learning.
• Experience analyzing multi-omic data types, including single-cell and spatial omics datasets.
• Experience using tools and frameworks for multi omic data analysis
• Experience programming in R and/or Python.
• Experience applying analytical, statistical, and/or machine learning methods to large-scale biological datasets.

Preferred Qualification

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

• Ability to derive and apply novel insights.
• Ability to critically evaluate cutting-edge tools and frameworks.
• Track record of writing reproducible and scalable code.
• Strong interpersonal and communication skills.
• Ability to thrive in a matrix environment.
• Demonstrated scientific capability as evidenced by publications, research reports, and external presentations.
• Demonstrated delivery of high quality and state-of-the-art computational biology solutions and analyses in support of drug discovery projects.
• Demonstrated experience in the analysis of multi-omic data linked to clinical phenotypes or measures for disease endotyping, biomarker discovery, mechanism and efficacy analysis and/or patient stratification.
• Demonstrated experience in the analysis of multi-omic data from clinical studies and working in a regulatory environment.
• Expertise in statistical approaches to the identification and assessment of predictive and prognostic biomarkers.
• Experience in application of agentic tooling for computational delivery.

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.

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.