PhD student under supervision of Charles Baroud in the team Physical microfluidics and Bioengineering. I mainly work on the development of quantitative assays using microfluidic devices to study T cell / cancer interactions.Main highlights:- Leading a project on immuno-oncology establishing quantitative biological assays to measure primary CD8+ T cells cytotoxicity against 3D models of tumor using a cancer-on-a-chip platform.- Using microscopy (time-lapse, bright-field, epifluorescence and confocal), image processing and data analysis using Python.- Quantitative analysis of T cell motility.- Multidisciplinary, collaborative and symbiotic research involving biologists and physicists.- Working in a public-private consortium (https://rhu-organomic.com/) on CAR-T cells cytotoxicity against patient-derived-organoids (PDOs).- 2D / 3D cell culture of patient-derived cells and murine cell lines.- Performing genetic modification of PDOs using Cripsr-Cas9.- Several multidisciplinary collaborations on image processing and data analysis. In particular, I developed and used a deep-learning based segmentation and classification pipeline to describe quantitatively the spatial organisation of biological tissues (https://github.com/BaroudLab/Pyxidis).- Scientific writing- Communication (oral/posters) at international conferences: Cargese France (2022), Grenoble France (2022), Harrogate UK (2023), Saarbrücken Germany (2023).

I am working on establishin patient-derived organoids coculture with CAR-T cells in a microfluidic device to study mechanisms of immune cells and cancer cells interactions that can be relevant to understand patient response to cell therapies.

Teaching mathematical tools for physics and fluid mechanics to 1st and 3rd year bachelor students.

Working on an image analysis tool to describe cell organisation in tissues using a network representation.

Research internship in biophysics with Maxime Deforet.- I developed an image analysis tools using Matlab to segment and track bacteria.- I used clustering analysis to describe quantitatively their organization within a monolayer colony.

Working on comparing radiation dose received by patients with simulations using Python.