European Research Council part-funded PhD Studentship: Deep Learning-Based Synthetic Histology for Microstructural MRI Biomarkers of the Liver King’s College London in United Kingdom

This European Research Council part-funded PhD studentship, titled “Deep Learning-Based Synthetic Histology for Microstructural MRI Biomarkers of the Liver,” is hosted at King’s College London within the Faculty of Life Sciences & Medicine. The project is supervised by Dr Andrada Ianus (School of Biomedical Engineering & Imaging Sciences) and Dr Cheng Zhang (The Roger Williams Institute of Liver Studies), offering a unique opportunity to join a dynamic, multi-disciplinary team with access to state-of-the-art imaging facilities and world-renowned expertise.

The research aims to advance the detection and characterisation of liver micrometastases in cancer by integrating advanced MRI techniques with computational histology. The PhD project focuses on developing a histology-informed simulation framework for multi-parametric MRI, leveraging deep learning to generate synthetic histology meshes. These meshes will be used to build MR signal dictionaries, enabling the estimation of tissue cellular properties from in vivo MRI data in a non-invasive manner. The approach will be applied to both preclinical and clinical MRI datasets, with results compared against histological ground truths to provide descriptors that outperform traditional models. This work is expected to significantly contribute to precision oncology and early metastasis detection.

Funding for this studentship is provided for three years, including a generous tax-free stipend of £26,881 per year, a Research Training Support Grant for consumables and conference attendance, and a budget for project-related expenses. However, tuition fees are not covered and must be self-funded (£8,000 for Home students and £34,700 for Overseas students in 2026/27, with annual increases up to 7%). Overseas students are also responsible for UK Visa and NHS Surcharge fees.

Applicants should have a strong academic background in biomedical engineering, medical imaging, computer science, or related fields. Experience with deep learning, MRI, and computational methods is highly desirable. The entry point for the position is October 2026, and the application deadline is April 17, 2026. For further information and to apply, candidates should visit the institution website and review all eligibility and funding details.

This studentship offers the chance to contribute to cutting-edge research in biomedical engineering and medical imaging, with a focus on developing innovative biomarkers for liver cancer metastasis. Successful candidates will benefit from a collaborative research environment, access to advanced facilities, and opportunities for professional development through conference participation.