Advancing Organoid Research through 3D Micro-Electrical Impedance Tomography for Dynamic, Label-Free, and Non-Invasive Phenotyping

Organoids are transforming biomedical research by providing three-dimensional (3D), human-relevant models of tissue development, physiology, and disease. However, their characterization still relies heavily on fluorescence labelling, microscopy, and destructive endpoint assays, limiting the ability to continuously monitor the same biological sample over time.

This PhD project aims to advance 3D micro-electrical impedance tomography (3D-μEIT) as a real-time, non-invasive, and label-free bioimaging technology for dynamic phenotyping of living organoids. Using a newly developed 3D-μEIT platform at imec, the project will investigate organoid development, maturation, and disease progression in selected disease models.

Unlike conventional imaging methods that primarily visualize morphology, 3D-μEIT measures spatial and temporal changes in tissue electrical impedance, providing insight into biological processes such as cell proliferation, apoptosis, extracellular matrix remodelling, fibrosis, barrier formation, and inflammation. This enables functional characterization beyond structural imaging alone.

The project combines organoid and stem cell biology, microsystems engineering, computational modelling, signal processing, and 3D image reconstruction. The candidate will establish relevant organoid models, identify biologically meaningful impedance-based biomarkers, and validate findings using established molecular and imaging techniques. Applications may include monitoring organoid growth, differentiation, viability, tissue organization, barrier integrity, inflammatory responses, fibrosis, and treatment effects.

A key component of the research will be the reconstruction and interpretation of complex 3D impedance datasets using MATLAB or Python. The candidate will explore advanced approaches such as AI-assisted image reconstruction, multimodal data integration, and longitudinal phenotypic analysis, enabling continuous monitoring of individual organoids and earlier detection of subtle biological changes.

We seek a highly motivated candidate with a background or strong interest in stem cell biology, organoid culture, tissue engineering, bioengineering, biomedical imaging, computational biology, or related disciplines. Experience with MATLAB, Python, or quantitative data analysis is advantageous. Candidates from both biological and engineering backgrounds are encouraged to apply.

The successful candidate will join a multidisciplinary team spanning MEMS technology, microelectronics, signal processing, electrochemistry, microfluidics, and stem cell biology, with access to imec's world-class research infrastructure. This project offers a unique opportunity to develop expertise at the interface of biology, engineering, and data science while contributing to next-generation semiconductor-enabled technologies for biomedical innovation.

Ultimately, the project seeks to establish 3D-μEIT as a powerful platform for dynamic organoid phenotyping, supporting mechanistic disease research, therapeutic response assessment, drug discovery, and precision medicine. The position offers opportunities for high-impact publications, international collaborations, and conference presentations.