About Us
The Faculty of Life Sciences & Medicine at King’s College London seeks to appoint a Research Fellow in the Comprehensive Cancer Centre, which is the academic arm of one of the leading cancer centres in Europe bringing together world-class clinical services delivered by our NHS partners, with research and education for the benefit of cancer patients in South East London and beyond.
The Wellcome Bioimaging project to accelerate cutting-edge bioimaging technology development, is a five-year cross-disciplinary programme, led by Professor Maddy Parsons from the School of Basic & Medical Biosciences (King’s College London). It will develop pioneering approaches to enable the creation of full molecular ‘maps’ of disease tissue, spanning multiple scales from whole organ down to individual molecules.
Human physiology is governed by thousands of dynamic components interacting across vast biological scales. While advances in imaging and molecular profiling have transformed individual disciplines, the resulting discoveries often remain fragmented and disconnected.
Our programme seeks to bridge these gaps through scale-crossing, multimodal spatial interrogation of human cells and tissues in three dimensions. Working across two exemplar disease areas, we will integrate clinical and medical imaging, with spatial transcriptomics and multi-omics multiplex imaging and digital pathology, and longitudinal clinical data.
The resulting datasets will form high-dimensional spatial atlases that connect molecular processes to cellular interactions, tissue architecture, biomechanics, and organism-level function. These integrated models will reveal emergent biological properties, identify novel therapeutic targets, and establish new approaches for understanding complex human disease.
About the Role
We are seeking an exceptional Computer Scientist, Computational Biologist, AI Researcher, or Data Scientist to join a pioneering interdisciplinary programme that aims to revolutionise our understanding of human physiology and disease.
This ambitious initiative will create an entirely new framework for understanding human biology by integrating data across molecular, cellular, tissue, organ, and whole-body scales. By combining advanced clinical imaging, multimodal spatial profiling, and functional analysis of human tissues, we will generate unprecedented insights into the mechanisms that govern health and disease.
The successful candidate will play a central role in developing the computational foundations required to integrate, analyse, model, and share some of the most complex biological datasets ever assembled.
This is a full time and you will be offered an a fixed term contract until 31 March 2031.
About You
To be successful in this role, we are looking for candidates to have the following skills and experience:
Essential Criteria
- Significant experience in analysing imaging-based data, including spatial transcriptomics data generated using platforms such as CosMX and Xenium. This should include experience with techniques such as image denoising, cell segmentation and the analysis of cellular neighbourhoods and cell–cell interactions.
- Experience in developing artificial intelligence and machine-learning methodologies for multimodal data.
- Experience collaborating with academic partners to apply novel mathematical, statistical, machine-learning and artificial intelligence techniques to relevant research problems.
- Strong programming skills and experience developing reproducible and scalable computational workflows for the analysis of complex biomedical data.
- Experience of using high-performance computing.
- A proven ability to lead research programmes and supervise researchers.
Desirable Criteria
- Knowledge of multimodal data integration, including integration of cell-based data with imaging-based data, and the use of topological and geometric frameworks (e.g., persistent homology, Ricci flow) to characterise tissue architecture and spatial organisation in transcriptomics data.
- Experience analysing radiological imaging data, particularly MRI, and integrating radiological imaging with digital pathology, spatial transcriptomics or other molecular data.
- Experience mentoring colleagues on bioinformatics projects and providing bioinformatics support to researchers from non-computational backgrounds.
- Experience working in multidisciplinary teams and presenting complex data to audiences from different disciplinary backgrounds.
- Strong organisational skills and attention to detail.
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