Research Engineer in Microscopy

laboratoire PhLAM, université de Lille

6 Jan 2024
Job Information

laboratoire PhLAM, université de Lille
Research Field
Researcher Profile
Recognised Researcher (R2)
Application Deadline
31 Jan 2024 – 23:00 (UTC)
Type of Contract
To be defined
Job Status
Hours Per Week
To be defined
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

Offer Description

Cell is the core unit of life and biological function arises from the dynamics of inter-connected biochemical reactions. Such biochemical circuits drive basic cellular functions (cell cycle, differentiation, stress response, …) and integrate multiple signals from cellular environment. In order to design new therapeutic strategies it is crucial to understand how biochemical circuits orchestrate in space and time biological functions.

Although cancer originate from dysregulated biological circuits, tumor progression and emergence of metastasis is still driven by a complex set rules arising from biochemical networks. For example, within a tumor, a small subset of cells called Cancer Stem Cells (CSC) are known to play a central role in tumor progression, resistance to treatment and metastasis. Indeed as opposed to Cancer Differentiated Cells (CDC), the CSC phenotype is necessary to regenerate a new tumor with an heterogeneity comparable to the original one. The CSC phenotype is very dynamic and is known to be contolled by several factors such as micro-environment or metabollic context. Evidences of transition from CDC to CSC one have been observed upon several kind of treatments. Moreover intra-cellular noise adds a stochastic component and contributes in shaping the tumor population.


In this project we aim at deciphering the key deterministic factors that allow maintenance of the CSC pool. For this we have setup live 2D microscopy experiments with a fluorecent reporter of the CSC phenotype. We imaged a population ~10⁴ cancer cells for up to 5 days. By means of image processing we extract the position and phenotype of each cells as a function of time. Using spatial point pattern analysis we have revealed mutual exclusion between CSC and CDC phenotypes. Moreover using machine learning frameworks such as Stochastic Force Inference (SFI) [1,2] we are able to quantitatively evaluate the respective role of cell to cell signaling and biochemical noise in CSC reprograming.Our set of quantitative tools revealed powerful to better understand how tumor heterogeneity arises in vitro.


A next step require monitoring dynamics of phenotype switches in micro-tumors grown in a context relevant for in vivo comparison. Tumoroid systems that mimic the tumor micro-environment can indeed be used to test therapeutic strategies [3]. To do so we will build a 3D imaging platform, based on non-linear light sheet microscopy, to monitor and analyze spatial dynamics of CSC reprogramming at single cell level and with high-throughput.

The offer is for 3 + 3 months.


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laboratoire PhLAM, université de Lille

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