Bioinformatics and Bioimage Analysis Engineer

Offer Description

18-month Engineer Position – Bordeaux, France

Field: Bioinformatics, Cancer Biology, Cancer Metabolism, Multi-Omics

Contract: 18 months

Location: University of Bordeaux, Bordeaux, France

Laboratory: INSERM – Oncodermatology Research Team

Research Environment

Our research team focuses on translational research in oncodermatology, with a particular interest in cutaneous carcinogenesis, cancer metabolism, and tumor heterogeneity. The team works in close collaboration with the Department of Dermatology at Bordeaux University Hospital and has access to well-characterized clinical cohorts, experimental models, and state-of-the-art omics and spatial biology platforms.

We are seeking a Bioinformatics and Bioimage Analysis Engineer to join a funded research program investigating the molecular and metabolic mechanisms underlying the development and progression of cutaneous squamous cell carcinoma (cSCC).

The successful candidate will contribute to the processing, analysis, integration, and biological interpretation of complex multi-omics and spatial datasets, with a particular emphasis on proteomics and metabolomics and their integration with spatially resolved molecular data. An important component of the position will also involve the computational analysis of multiplex tissue images, from image preprocessing and cell segmentation to spatial quantification and integration with molecular profiles.

Project Description

Growing evidence indicates that metabolic reprogramming plays a major role in tumor initiation, progression, and therapeutic response. However, the metabolic heterogeneity of cutaneous squamous cell carcinoma and the molecular events accompanying the transition from precancerous lesions to invasive tumors remain incompletely understood.

Our team has identified major metabolic alterations associated with cutaneous carcinogenesis and is investigating how these metabolic programs evolve during tumor progression and contribute to inter-patient and intra-tumoral heterogeneity.

Taking advantage of a well-characterized biobank comprising human skin samples representing different stages of cSCC carcinogenesis, the project combines complementary proteomic, metabolomic, transcriptomic, and spatially resolved molecular approaches.

The recruited engineer will play a central role in analyzing these datasets, identifying molecular and metabolic signatures associated with tumor progression, and integrating complementary omics layers to characterize the spatial organization and metabolic heterogeneity of cSCC.

Particular attention will be given to the integration of proteomic and metabolomic profiles with spatial transcriptomic datasets, with the objective of linking metabolic states to specific tumor regions, cellular populations, and stages of carcinogenesis.

The project ultimately aims to identify metabolic vulnerabilities and molecular signatures that may contribute to improved patient stratification and the development of new therapeutic strategies for cSCC.

Main Responsibilities

The Bioinformatics Engineer will work closely with biologists, clinicians, bioinformaticians, and platform scientists and will be involved in:

• Processing and statistical analysis of quantitative proteomics and metabolomics datasets.
• Differential expression/abundance analyses and identification of molecular signatures associated with disease progression.
• Pathway, functional enrichment, and network analyses.
• Processing and quantitative analysis of multiplex and spatial tissue images, including image registration/alignment, quality control, cell and nuclear segmentation, signal quantification, and extraction of single-cell features.
• Cell phenotyping and spatial analysis of the tumor microenvironment, including cellular distribution, neighborhood relationships, co-expression patterns, and spatial heterogeneity.
• Development or adaptation of image-analysis workflows using tools such as QuPath, ImageJ/Fiji, or equivalent computational imaging frameworks.
• Analysis and interpretation of spatially resolved transcriptomic and molecular datasets, from raw or intermediate data to biologically interpretable results.
• Integration of image-derived features and spatial molecular information with proteomic, metabolomic, and transcriptomic datasets.
• Development and implementation of reproducible workflows for multi-omics and bioimage data analysis.
• Data visualization and generation of publication-quality figures and spatial maps.
• Biological interpretation of results in close interaction with experimental researchers and clinicians.
• Contribution to scientific publications and presentation of results.

Research Environment and Resources

• The successful candidate will join a multidisciplinary and collaborative environment combining expertise in cancer biology, dermatology, metabolism, bioinformatics, proteomics, spatial biology, and translational research.
• The team has access to technological platforms for proteomics, metabolomics, spatial and single-cell analyses, microscopy, flow cytometry, experimental pathology, and preclinical models. The close interaction with Bordeaux University Hospital provides access to clinically characterized patient samples and facilitates translational research.

Selected Recent Publications

• Naji et al. bioRxiv (2026). DOI: 10.64898/2026.04.30.721943
• Dousset et al. British Journal of Dermatology. PMID: 40577595
• Khalife et al. Cell Death & Disease. PMID: 42049699
• Hosseini et al. Oncogenesis. PMID: 31551419
• Mahfouf et al. Journal of Investigative Dermatology. PMID: 30878676
• Hosseini et al. Cell Reports. PMID: 29925003

Where to apply

E-mail: hamid-reza.rezvani@u-bordeaux.fr

Requirements

Research Field: Other

Education Level: Master Degree or equivalent

Skills/Qualifications

Applicants should hold a Master's degree or equivalent qualification in Bioinformatics, Computational Biology, Bioimage Analysis, Biostatistics, Systems Biology, or a related field.

The ideal candidate will have:

• Strong skills in R and/or Python for biological data analysis.
• Experience in statistical analysis and visualization of high-dimensional biological datasets.
• Experience with proteomics and/or metabolomics data analysis.
• Experience or strong interest in biomedical image analysis, particularly fluorescence, multiplex imaging, or digital pathology.
• Familiarity with image-processing concepts such as image registration, segmentation, feature extraction, signal quantification, and cell phenotyping.
• Experience with QuPath, ImageJ/Fiji, CellProfiler, or related image-analysis tools would be highly appreciated.
• Knowledge of pathway and functional enrichment approaches.
• Experience with transcriptomic data analysis, including single-cell or spatial transcriptomics, would be highly appreciated.
• Experience in spatial data analysis and/or multi-omics integration would be a strong advantage.
• Familiarity with cancer biology, metabolism, or molecular and cellular biology would be advantageous.
• Ability to develop reproducible and well-documented computational workflows.
• Ability to work with both raw/processed imaging data and quantitative molecular datasets, rather than exclusively pre-generated expression matrices.
• Ability to work independently while interacting closely with experimental biologists, clinicians, and technology platforms.
• Good written and spoken English.

Experience with spatial omics, multiplex tissue imaging, digital pathology, or computational approaches for studying tumor heterogeneity would be considered a strong asset.

A strong biological understanding and an interest in translating computational and imaging results into mechanistic hypotheses are particularly important for this position.

Languages: ENGLISH

Level: Good

Research Field: Biological sciences » Biology

Years of Research Experience: 1 - 4

Additional Information

Selection process

Interested candidates should submit:

• A curriculum vitae;
• A cover letter describing their previous research and bioinformatics experience, relevant computational skills, and motivation for joining the project;
• Contact information for two referees or two supporting letters.

Applications should be sent to Hamid-Reza REZVANI (hamid-reza.rezvani@u-bordeaux.fr).

Work Location(s)

Number of offers available: 1

Company/Institute: Université de Bordeaux-Inserm U1312

Country: France

City: Bordeaux

Postal Code: 33000

Street: 2 Rue Dr Hoffmann Martinot

Geofield

Contact

State/Province: BORDEAUX

City: Bordeaux

Website: https://www.bricbordeaux.com/en/

Street: 146 rue Leo Saignat

Postal Code: 33076

E-Mail: hamid-reza.rezvani@u-bordeaux.fr

Phone: 0557575683