9 Sep 2026
Job Information
Organisation/Company: CNRS
Department: Centre de Recherche En Acquisition et Traitement de l'Image pour la Santé
Research Field: Pharmacological sciences; Engineering; Technology
Researcher Profile: First Stage Researcher (R1)
Application Deadline: 29 Sep 2026 - 23:59 (UTC)
Country: France
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 35
Offer Starting Date: 1 Nov 2026
Is the job funded through the EU Research Framework Programme?: Not funded by a EU programme
Is the Job related to staff position within a Research Infrastructure?: No
Offer Description
Context
Cancer is the leading cause of death in France, and early detection is crucial for improving survival. Early imaging-based assessment of treatment efficacy—through markers such as cell death or tumor modification—would enable rapid confirmation of therapeutic response and, in non-responding tumors, allow timely adjustment of therapy without waiting for postoperative pathological evaluation, as often occurs with bone sarcomas.
Quantitative ultrasound (QUS) parameters derived from ultrasound measurements of the backscatter coefficient (BSC) have been shown to be useful for monitoring anti-cancer therapies that induce apoptosis or mitotic catastrophe, for example [1,2]. In particular, these parameters have been used to show whether or not preclinical or clinical breast cancer tumors are responding to therapy [3]. Ultrasound parameters derived from BSC and envelope statistics are related to tissue microstructure [4] and may therefore be of interest for assessing necrosis or morphological changes of the tissue due to the therapy as an efficacy criterion of conventional therapy or for evaluating new therapies that affect tumors microstructure differently. In a previous study [5], we highlighted changes in ultrasound parameters on osteosarcoma were associated with changes in chromatin and collagen condensation in tumors that ultimately showed unresponsive to therapy.
MRI imaging, as diffusion-weighted MRI (DW-MRI) is sensitive to macromolecular and microstructural changes which can occur at the cellular level even earlier than anatomical changes during therapy. DWI-MRI provides the apparent diffusion coefficient (ADC) that measures water diffusion and tends to decrease in tissues with high cellularity. This technique shows promise for evaluating cancer treatment response via the quantification of ADC values [6–8]. Magnetic resonance elastography (MRE) is a noninvasive technique that quantifies tissue biomechanical properties. Tissue stiffness undergoes significant changes during the development and progression of cancer, and MRE has been used to detect and characterize malignant tissue, assess treatment response and explore the underlying tissue biomechanics of tumors [9,10].
Osteosarcomas are particularly resistant to conventional treatments. Despite aggressive therapeutic protocols, combining surgery and chemotherapy, the 5-year survival rate for patients with metastatic or relapsed osteosarcoma remains below 30%. Recent advances in immunotherapy have shown promise in their treatment. For instance, immunomodulatory approach can induce significant changes in the tumor microenvironment that can disrupt the tumor's immune evasion mechanisms, creating an environment more conducive to therapeutic efficacy [11]. The osteosarcoma model provides a particularly robust framework for validating our imaging-based approach. Its exceptionally high rate of therapeutic resistance (60–70% non-responders) makes it an ideal stress test—if imaging biomarkers prove effective here, they are likely to be applicable to more responsive tumors. Osteosarcoma also offers a clear and standardized pathological reference for treatment response (Huvos grade), enabling strong ground-truth validation. In addition, its highly heterogeneous microenvironment, located at the bone–soft-tissue interface, creates a particularly challenging environment for imaging-based analyses. The mechanisms of resistance are well characterized and relevant to other sarcomas, further reinforcing the model's translational value. Finally, established murine models such as MOS-J provide reliable and reproducible tumor growth patterns, ensuring experimental consistency.
Therefore, the central hypothesis in the CUMBA project is that cancer therapy triggers a cascade of biological changes that manifest as measurable physical properties (illustrated in Figure 1 (left panel)). Treatment-induced cell death decreases tissue cellularity, reducing both acoustic impedance (US-detectable) and tissue stiffness (MRE-measurable). Simultaneously, extracellular matrix degradation alters collagen architecture, modifying backscatter coefficient. Immune infiltration and vascular remodeling create spatial heterogeneity potentially detectable across all modalities. We propose that ultrasound spectroscopy and multiparametric MRI provide complementary windows into this biological remodeling: US parameters (BSC, Nakagami parametres) reflect microscopic tissue organization (cell size, nuclear condensation), while MRI captures tissue-scale properties (stiffness via MRE and diffusion and perfusion via DW MRI). This multimodal signature will be more sensitive than individual parameters because each modality probes different aspects of the same underlying biological response, creating a comprehensive picture of treatment efficacy detectable before tumor shrinkage. The innovation lies in mechanistically linking these physical measurements to resistance pathways: early non-responders will show distinct imaging patterns corresponding to specific molecular signatures (identified through RNA-Seq), enabling predictive biomarker development.
Postdoctoral Position Objective
We propose a 2-year postdoctoral position focused on ultrasound and MRI acquisition and post-processing, as well as investigating the relationship between imaging and biological parameters.
The postdoctoral fellow will work on the design and improvement of the ultrasound and MRI imaging acquisition setup. An initial study enabled MRI diffusion, ERM, and ultrasound measurements on osteosarcoma tumors but requires improvements, notably the implementation of a higher-frequency ERM setup, in vivo ultrasound attenuation measurements, and multi-frequency ultrasound measurements.
Supervision
The post-doc will be supervised by Pauline Muleki Seya (Ultrasound imaging team) and Pilar Sango Solanas (MRI team) in collaboration with Aurélie Dutour (Cancer Research Center in Lyon). Ultrasound and MRI acquisitions will be realized in CREATIS PILoT platform on mice.
Where to apply
Website: https://emploi.cnrs.fr/Offres/CDD/UMR5220-PAUMUL-005/Default.aspx
Requirements
Research Field: Pharmacological sciences
Education Level: PhD or equivalent
Research Field: Engineering
Education Level: PhD or equivalent
Research Field: Technology
Education Level: PhD or equivalent
Languages: FRENCH
Level: Basic
Research Field: Pharmacological sciences
Years of Research Experience: None
Research Field: Engineering
Years of Research Experience: None
Research Field: Technology
Years of Research Experience: None
Additional Information
Eligibility criteria
Candidate profile
The candidate should ideally hold a degree in engineering, or equivalent, with a specialization in biomedical imaging, particulary in ultrasound and/or MRI acquisition and signal processing. The candidate must be able to work independently and have knowledge of MATLAB programming and signal/image processing. Experience or skills in medical applications are appreciated. Please note that this postdoctoral position will involve a significant amount of experimental work, including animal experiments on mice.
Website for additional job details: https://emploi.cnrs.fr/Offres/CDD/UMR5220-PAUMUL-005/Default.aspx
Work Location(s)
Number of offers available: 1
Company/Institute: Centre de Recherche En Acquisition et Traitement de l'Image pour la Santé
Country: France
City: VILLEURBANNE
Contact
City: VILLEURBANNE