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

At GSK, our mission is to improve the quality of human life by enabling people to do more, feel better, and live longer. We are a science-led global healthcare company with a special purpose: to help people do more, feel better, live longer.

We are seeking a Principal Scientist - Spatial Multiomics (m/f/d) with extensive expertise in Machine Learning (AI/ML) and computer vision applications to histology and spatial biology to lead the development and deployment of deep learning solutions to transform raw histological images and spatial omics datasets (spatial transcriptomics, proteomics, and metabolomics) into analysis-ready data for drug discovery and disease phenotyping. The candidate will architect end-to-end machine learning pipelines and play a crucial role in data processing workflows across different tissues, applying modern AI/ML frameworks specifically to tissue microenvironment analysis, cell-cell interaction modeling, and disease phenotype prediction to inform target discovery and the development of complex in vitro models. This role requires hands-on expertise working at the intersection of computational biology and artificial intelligence, combining deep biological understanding with practical AI/ML engineering skills, and the ideal candidate will have a strong background in data pipelines for applied machine learning, digital pathology, histology and tissue biology.

Key Responsibilities:

• Lead the development and deployment of advanced machine learning pipelines to transform raw histological images and spatial omics datasets into quantitative, analysis-ready insights that directly inform target validation strategies and drug discovery decision-making.
• Design and implement end-to-end computational workflows for processing multi-modal spatial data (transcriptomics, proteomics, metabolomics) across diverse tissue types, ensuring robust data quality, reproducibility, and scalability to support high-throughput target screening and validation programs.
• Explore specialsed generative AI/ML approaches for tissue microenvironment characterisation, cell-cell interaction modeling, and disease phenotype prediction for target prioritisation, mechanism of action studies, and therapeutic hypothesis generation.
• Establish and maintain cutting-edge methodological capabilities by staying current with advancements in spatial multiomics, digital pathology, and AI/ML frameworks, continuously evaluating and implementing new technologies.
• In close collaboration with other analytical teams, communicate analytical results to stakeholders through compelling data presentations.

Qualifications:

• PhD in a relevant field (e.g., Computational Biology, Systems Biology, Biology, Medicine) with a strong emphasis on machine learning and spatial multiomics.
• Full command of programming languages with emphasis on the Python ecosystem.
• Extensive experience in spatial omics data processing workflows.
• Proven track record in disease phenotyping and digital pathology through peer-reviewed publications and/or AI/ML conferences.
• Expertise in applied machine learning workflows, particularly pytorch and pytorch-geometric is essential.
• Strong analytical and problem-solving skills focused on linking different data modalities to extract disease-specific biological insights.
• Knowledge of coding best practices and documentation (i.e: github, gitlab).  
• Excellent communication and collaboration skills, with the ability to work effectively in multidisciplinary teams.

• Opportunity to work in a cutting-edge scientific environment with access to state-of-the-art technologies.
• Collaborative and inclusive culture that values innovation and scientific excellence.
• Competitive compensation and benefits package.
• Commitment to professional development and career growth.

How to Apply: If you are passionate about spatial multiomics and excited about the opportunity to contribute to groundbreaking research at GSK, we encourage you to apply. Please submit your resume and a cover letter outlining your qualifications and experience. Please also include a link to the github repository of a project you recently contributed. Candidates that do not provide this will not be considered.

Application Deadline: 9th July 2025

GSK is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Join us in our mission to improve lives through science.

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Why GSK?

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

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

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