Postdoctoral Researcher (M/F)

Job Description

Missions

The postdoctoral researcher will develop and implement bioinformatic and statistical approaches to identify reproducible spatial patterns, metabolic niches and associations between the tumour and its environment across different experimental models and datasets.

Activity

• To analyse spatial omics datasets, including spatial transcriptomics and mass spectrometry imaging data from glioblastoma models. This work will focus in particular on the spatial representation of molecular signals, the characterisation of regions and niches, and the comparison of spatial patterns across samples and experimental conditions.
• Develop and apply quantitative approaches to spatial organisation. The postdoctoral researcher will investigate spatial associations between molecular programmes, tumour regions and microenvironmental components using spatial statistics, graph representations and multi-scale analyses.
• Integrate multimodal datasets, including those from spatial transcriptomics, metabolomics/lipidomics, molecular profiles and complementary imaging data, with the aim of identifying biologically coherent and reproducible patterns across modalities and experimental models.
• To assess robustness and reproducibility, in particular through comparisons between biological replicates, spatial scales, technologies and analytical approaches. The postdoctoral researcher will contribute to the development of quantitative criteria for assessing the stability of spatial signatures and candidate interactions between the tumour and the microenvironment.
• Contribute to biological interpretation and experimental validation. The postdoctoral researcher will work closely with biologists specialising in glioblastoma to translate computational results into experimentally testable hypotheses, prioritise candidate spatial or metabolic programmes, and interpret validation results.
• Develop reproducible computational workflows, document methods and results, manage code under version control, and contribute to open-source software, scientific figures, consortium reports and publications.

Your Profil

Skills

The candidate must hold a PhD in bioinformatics, computational biology, biostatistics, applied mathematics, computer science or a related discipline, and have proven experience in the quantitative analysis of biological data.
This post is particularly suited to candidates interested in the spatial organisation of biological systems and in the development of analytical approaches, rather than simply applying existing pipelines.
Required skills:
• In-depth proficiency in R and/or Python for statistical analysis, data processing and visualisation.
• A solid grounding in statistics and quantitative data analysis, including the ability to critically assess robustness, variability and potential confounding factors.
• Experience in analysing high-dimensional biological data and designing reproducible computational workflows.
• Ability to formulate spatial or biological questions quantitatively and translate them into appropriate computational analyses.
• Ability to integrate heterogeneous datasets and link computational models to biological interpretation.
• Scientific autonomy, critical thinking and the ability to work closely with experimental researchers.
• Good command of written and spoken English, including the ability to present results and contribute to scientific publications. Level C1 of the Common European Framework of Reference for Languages (CEFR)

Additional skills that would be an advantage:
Experience in spatial transcriptomics, spatial statistics, image-based spatial analysis, single-cell genomics, metabolomics, mass spectrometry imaging, graph-based modelling or multimodal data integration would be particularly relevant. Experience in representation-based learning, metabolic pathway analysis or computational approaches to tumour-microenvironment interactions would also be an asset.

Expertise in all these areas is not required. A strong quantitative background, experience with spatially resolved biological data and an interest in methodological development are the main priorities.

Your Work Environment

The postdoctoral researcher will be based at the IBGC in Bordeaux, working closely with the computational biology and bioinformatics team led by Dr Macha Nikolski and the GBmetabo team led by Dr Thomas Daubon.
This post forms part of the ShadowEV-GBM project, funded by INSERM. It is an interdisciplinary research project coordinated by the IBGC (CNRS, Bordeaux) and bringing together experts in bioinformatics, glioblastoma biology, metabolism, extracellular vesicles and spatial omics.
Glioblastoma invasion is strongly influenced by interactions between tumour cells and the brain microenvironment, particularly along myelin-rich white matter structures. ShadowEV-GBM aims to understand how spatially organised metabolic programmes and communication between the tumour and its microenvironment contribute to invasion, by combining spatial transcriptomics, mass spectrometry imaging, metabolomics/lipidomics, molecular profiling and experimental models.
We are seeking a postdoctoral researcher with a strong background in computer science to contribute to the spatial and integrative analysis of these multimodal datasets.
The project provides access to original spatial multi-omic datasets, notably from spatial transcriptomics and mass spectrometry imaging of glioblastoma invasion, as well as complementary molecular and experimental data. The postdoctoral researcher will work in close collaboration with the researchers who generated these datasets, as well as with project partners specialising in the biology of extracellular vesicles and functional validation.
The computing environment relies on the infrastructure of the Bordeaux Bioinformatics Centre (CBiB) for data storage, high-performance computing and reproducible analysis. This post offers numerous opportunities for methodological development in spatial bioinformatics and multimodal data integration, with the aim of producing both biological insights and computational methods, as well as reusable software.

Compensation and benefits

Compensation

Between €3,041.58 and €4,216.70 gross per month, depending on experience

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

The research professions