We hire - Engineer (Ingénieur d'Études) in Image Processing

Keywords: 4D (space + time) image processing, segmentation and tracking, confocal microscopy, lignocellulosic biomass

Hosting laboratory: FARE Laboratory, INRAE / URCA, 2 esplanade Roland-Garros, 51100 Reims, France.

Duration: 18 months (with a potential 6-month extension )

Deadline: open until filled

Salary: 2200 to 2400 € (gross salary) depending on experience

Context
The environmental and economic challenges of climate change, and the growing global demand for energy, underscore the importance of a green transition from fossil carbon sources to alternative energy and material sources. The transformation of plant cell wall into bioproducts can be a sustainable, and carbon-neutral solution by recycling atmospheric CO2, and by cutting down our reliance on oil. A major challenge in converting the plant cell wall to bioproducts is the resistance of the plant cell wall, known as recalcitrance, which increases the cost of conversion.

Over the past decades, extensive research has focused on plant cell wall recalcitrance, leading to the identification of key recalcitrance markers such as cell wall porosity and lignin content [1]. Notably, investigations have predominantly focused on markers at the nano-scale, while the enzymatic hydrolysis of plant cell wall at the cell and tissue scales remains under-investigated. Our team has recently overcome the experimental and computational challenges of studying the enzymatic deconstruction at micro-scale by developing a 4D (space + time) imaging pipeline including time-lapse fluorescence confocal imaging, and 4D image processing involving segmentation and tracking to identify key cell scale parameters underlying cell wall deconstruction [2].

Engineer Mission

Starting from this pipeline and the already available 4D dataset, the successful candidate will further develop the pipeline to extract the dynamics of voxel intensity representing plant cell wall deconstruction captured in time series. The extracted values will be used to extract cellular structural parameters (e.g. cell wall thickness, neighbour numbers). A correlation analysis between the temporal evolution of voxel intensities and structural cell parameters will be conducted.

This engineer position is part of the FillingGaps project (9 M€ budget) led by FARE laboratory and funded by the French National Research Agency (ANR) under the B-BEST programme. FillingGaps aims to develop multiscale approaches for model biomass species to achieve a deeper understanding of the factors governing biomass recalcitrance and the mechanisms underlying its deconstruction.

Requirements

Candidates should be completing a MSc in computer science, engineering, applied mathematics, or related fields. Applicants should have very good skills in Python. Experience in image processing would also be advantageous. Communication and reporting skills are essential as the successful candidate will need to work in an interdisciplinary team and write up progress reports and make oral presentations.

Application

Applicants should send a letter of motivation and a CV, including the contact details of at least two academic referees to supervisors:

Dr. Yassin Refahi, yassin.refahi@inrae.fr, +33 (0)3 26 77 35 86
Dr. Gabriel Paës, gabriel.paes@inrae.fr, +33 (0)3 26 77 36 25

References

[1] Zoghlami, Aya, and Gabriel Paës. "Lignocellulosic biomass: understanding recalcitrance and predicting hydrolysis." Frontiers in chemistry 7 (2019): 874. https://doi.org/10.3389/fchem.2019.00874

[2] Refahi, Yassin, et al. "Plant Cell Wall Enzymatic Deconstruction: Bridging the Gap Between Micro and Nano Scales." bioRxiv (2024): 2024-01. https://doi.org/10.1101/2024.01.11.575220