Principal Scientist (mfd) Spatial Multiomics

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 peoples 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. Were uniting science technology and talent to get ahead of disease together.

Principal Scientist (m/f/d) - Spatial Multiomics

In this position you will join a crossdisciplinary team to lead the design and implementation of advanced AI/ML solutions that transform raw histology images and spatial omics data into biologically interpretable analysisready datasets for drug discovery and disease phenotyping. You will architect endtoend machine learning pipelines and integrate modern deep learning frameworks into data processing workflows spanning spatial transcriptomics proteomics and metabolomics. Your work will focus on tissue microenvironment analysis modelling cellcell interactions and predicting disease phenotypes that directly inform target discovery and the development of complex in vitro models. The role sits at the intersection of computational biology and artificial intelligence requiring handson expertise in digital pathology histology and tissue biology together with practical AI/ML engineering skills to deliver scalable robust solutions for realworld translational impact.

Key Responsibilities

• Lead the development and deployment of advanced ML pipelines that convert raw histology images and spatial-omics datasets into quantitative biologically interpretable insights to support target validation and drug-discovery decision making
• Design and implement end-to-end computational workflows for multimodal spatial data (transcriptomics proteomics metabolomics) across diverse tissue types ensuring data quality reproducibility and scalability for highthroughput screening and validation
• Develop and apply specialised generative AI/ML methods for tissue microenvironment characterisation cellcell interaction modelling and disease phenotype prediction to produce quantitative evidence packages for target prioritisation and mechanismofaction studies
• Collaborate with biology analytical and clinical teams to translate computational results into actionable datasets (e.g. biomarkers patient stratification in vitro model readouts) that inform go/nogo decisions
• Maintain and enhance methodological capabilities by monitoring advances in spatial multiomics digital pathology and AI/ML frameworks and by evaluating and adopting new technologies to strengthen target validation outputs
• Drive crossfunctional integration of spatialomics insights into broader disease phenotyping and target discovery workflows to ensure coherent data flow and interpretation across platforms
• Communicate complex analytical findings and their implications to internal and external stakeholders via clear presentations publications and conference talks highlighting the value of spatial biology in target validation

Qualifications & Skills

• PhD in a relevant field (e.g. Computational Biology Systems Biology Biology Medicine) with a strong emphasis on machine learning and spatial multiomics
• Excellent programming skills with an emphasis on the Python ecosystem
• Extensive experience with spatial omics data processing workflows
• Proven track record in disease phenotyping and digital pathology demonstrated by peerreviewed publications and/or AI/ML conference contributions
• Strong expertise in applied machine learning workflows particularly with PyTorch and PyTorchGeometric
• Strong analytical and problemsolving skills focused on integrating multiple data modalities to extract diseasespecific biological insights
• Familiarity with coding best practices and documentation tools (e.g. GitHub GitLab)
• Excellent communication and collaboration skills with the ability to work effectively in multidisciplinary teams

Find out more:

• Annual Report
• Product Pipeline
• #EBDE

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 were 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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