# Computational Scientist - Spatial Omics and AI

**Company**: GSK
**Location**: Heidelberg
**Experience**: senior
**Job type**: full-time
**Salary**: EUR 88,500 to EUR 147,500
**Category**: Data Science
**Industry**: Healthcare

**Apply**: https://gsk.wd5.myworkdayjobs.com/en-US/GSKCareers/job/Heidelberg---Office/Scientific-Leader--Spatial-Omics---Computational-AI--m-f-d-_450507-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_80ef4b8a-169

## Description

GSK is seeking an experienced Computational Scientist to shape its Spatial Omics and AI capabilities.

You will lead a team developing scalable pipelines and innovative methods for complex single-cell and spatial omics data, enabling deeper insight into disease mechanisms, stronger target hypotheses, and more confident drug-discovery decisions.

Alongside hands-on technical development, you will set scientific direction, establish quality and reproducibility standards, and partner across disciplines to embed these capabilities in research programs and enable their effective use across studies.

**Key Responsibilities**

- Lead and develop a team of computational scientists, setting scientific priorities and ensuring high-quality delivery.

- Define the analytical strategy for Spatial Omics, establish scalable FAIR data-processing pipelines, and represent the group in cross-functional forums and discussions with senior stakeholders.

- Develop and apply advanced methods for diverse spatial omics (transcriptomics, proteomics, lipidomics, metabolomics) and digital pathology.

- Enable multimodal integration across single-cell, molecular, spatial, morphological, and pathology data.

- Deploy and develop agentic AI workflows that automate processing and orchestrate analyses.

- Partner with experimental scientists, disease biologists, pathologists, and technology teams to inform analytical and scientific strategy.

**Basic Qualifications**

- PhD in computational biology, data science, or related discipline.

- Strong grounding in disease biology, with the capacity to frame complex scientific questions and interpret multidimensional data in a biologically meaningful context.

- Demonstrated expertise in single-cell and/or spatial omics, supported by practical experience integrating multiple molecular data types.

- Advanced Python proficiency and a record of building reproducible analytical workflows with open-source scientific ecosystems such as scverse.

- Experience developing and deploying agentic scientific workflows at scale.

- Evidence of successful people or technical leadership, including mentoring, capability building, and accountability for team outcomes.

- Strong communication and collaboration skills across computational and experimental disciplines.

**Preferred Qualifications**

- Advanced experience linking spatial molecular profiles with histology, imaging-derived features, or digital pathology outputs.

- Ability to create data visualizations that communicate complex spatial and multimodal findings to scientific and decision-making audiences.

- Knowledge of machine learning for image analysis, multimodal integration, or predictive modeling in biomedical research.

- Track record of moving methodological innovation into adopted solutions that influence biological insight and drug-discovery decisions.

## Skills

### Required
- Python
- single-cell omics
- spatial omics
- data science
- computational biology
- biological data analysis
- AI
- machine learning

### Nice to have
- digital pathology
- image analysis
- multimodal integration
- predictive modeling
- data visualization

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Source: [Apply at gsk.wd5.myworkdayjobs.com](https://gsk.wd5.myworkdayjobs.com/en-US/GSKCareers/job/Heidelberg---Office/Scientific-Leader--Spatial-Omics---Computational-AI--m-f-d-_450507-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)