MULTIMODAL LABEL-FREE APPROACH FOR QUANTITATIVE ASSESSMENT OF CELLULAR VIABILITY USING HYPERSPECTRAL IMAGING AND BIO-IMPEDANCE ON A MICROFLUIDIC LAB-ON A-CHIP

Cell viability assessment is a major challenge in cell biology and biomedical research, particularly in the fields of drug screening and cellbased therapies. Conventional methods mainly rely on destructive assays or fluorescent labeling, which limit continuous monitoring of cell cultures.

Label-free approaches represent a promising alternative. Hyperspectral imaging (HSI) enables the extraction of optical signatures related to the morphological and metabolic state of cells, while bioelectrical impedance analysis (BIA) provides complementary information about their intracellular electrical properties. In this project, bioimpedance measurements are performed within an instrumented microfluidic chip integrating microelectrodes.

Although HSI and BIA have individually demonstrated their potential for label-free cell viability assessment, their combined integration into a microfluidic lab-on-a-chip device remains largely unexplored. This PhD project aims to develop a multimodal, non-destructive, and interpretable approach that combines optical and electrical measurements on a single chip.

L’Institut Jean Lamour (IJL) est une unité mixte de recherche du CNRS et de l’Université de Lorraine. Spécialisé en science et ingénierie des matériaux et des procédés, il couvre les champs suivants : matériaux, métallurgie, plasmas, surfaces, nanomatériaux, électronique.

En 2026, l'IJL compte 258 permanents (33 chercheurs, 133 enseignants-chercheurs, 92 IT-BIATSS) et 389 non-permanents (146 doctorants, 43 post-doctorants / chercheurs contractuels et plus de 200 stagiaires), de plus de 70 nationalités différentes. Il collabore avec plus de 150 partenaires industriels et ses collaborations académiques se déploient dans une trentaine de pays. Son parc instrumental exceptionnel est réparti sur 4 sites dont le principal est situé sur le campus ARTEM à Nancy.

The candidate must hold a Master’s degree (MSc, equivalent to Master 2) in: Electrical Engineering (EEA – Electronics, Electrical Engineering and Automation), with a specialization in: Electronics, Instrumentation, Biomedical Imaging and Signal and Image Processing

The candidate should have the following skills: Strong background in electronic instrumentation, measurement systems, and data acquisition

Good skills in signal processing and image processing

Proficiency in at least one scientific programming environment (Python or MATLAB)

Basic knowledge of machine learning / artificial intelligence

Knowledge in optics (imaging) will be particularly appreciated.