Researcher

LabAcute and Chronic Cardiovascular Failure (DCAC) (UMR_S 1116) / Multidisciplinary Clinical Investigation Center (CIC-P 1433) Job Description The recruited candidate will work on the alterations of the endothelial glycocalyx in heart failure with preserved ejection fraction (PMID: 40439171). Main Missions Analyze the degradation of the endothelial glycocalyx at different stages of heart failure with preserved ejection fraction (HFpEF), using specific biomarkers (syndecan-1, hyaluronan, hyaluronidase) and correlating them with echocardiographic measurements of diastolic function. Utilize and integrate clinical, biological, and proteomic data from large cohorts and clinical trials (STANISLAS, HOMAGE, ALDO-DHF, MEDIA-DHF) to understand the pathophysiological mechanisms associated with glycocalyx alterations. Implement complex network modeling and artificial intelligence (machine learning) approaches to characterize the biological interactions involved in HFpEF progression. Assess the impact of preventive therapeutic strategies (in particular, the use of mineralocorticoid receptor antagonists, MRAs) on the evolution of the endothelial glycocalyx and the pathophysiology of HFpEF. Develop an integrated risk stratification model, combining biological phenotyping, proteomic data, and imaging, to identify individuals at highest risk of developing HFpEF and those most likely to benefit from personalized preventive treatment. Activities Collect, organize, and harmonize data from various cohorts and clinical trials (STANISLAS, HOMAGE, ALDO‑DHF, MEDIA‑DHF). Setup and execute bioinformatic pipelines for the analysis of omics data (particularly proteomics) and integrate them with clinical and imaging data. Develop and apply statistical and machine‑learning methods to explore the links between glycocalyx degradation and HFpEF progression. Build complex biological network models to identify the pathophysiological mechanisms involved. Assess the effects of preventive treatments (MRAs) on glycocalyx dynamics by integrating biological, proteomic, and clinical data. Design an integrated predictive model to identify individuals at highest risk of developing HFpEF and those likely to benefit from targeted prevention. Document and ensure the reproducibility and traceability of bioinformatics analyses (scripts, workflows, code repositories). Work closely with clinicians, biologists, and researchers to interpret results and guide analyses. Write reports, figures, and scientific communication materials (publications, presentations, conferences). Position Specifics and Work Environment Work within the framework of an ANR‑funded project, at a Clinical Investigation Center, in a University Hospital, in contact with a multidisciplinary team of physicians, analysts, and basic researchers. Compliance with legal requirements related to health data. Adherence to the CIC‑P ISO9001 quality process. Knowledge Omics methods (proteomics, transcriptomics, metabolomics) and their analytical pipelines. Foundations in biostatistics and epidemiology applied to large clinical cohorts. Machine learning and artificial intelligence applied to biomedical data (classification, clustering, predictive modeling). Basics in medical imaging (echocardiography, cardiac MRI) and multimodal data integration. Skills Expertise in at least one scientific programming language: R, Python, or SAS. Experience in managing, processing, and integrating clinical, biological, and proteomic data. Expertise in advanced statistical analyses and biological network modeling. Use of machine‑learning libraries and frameworks (scikit‑learn). Proficiency with database management tools (SQL, NoSQL) and collaborative environments (Git/GitLab). Abilities Scientific rigor and critical thinking in interpreting results. Ability to work in an interdisciplinary setting (clinicians, biologists, bioinformaticians). Strong communication skills (presentation of results, scientific outreach). Autonomy, organization, and respect for deadlines in a collaborative research environment. Scientific curiosity and interest in therapeutic innovation and precision medicine. Experience Previous postdoctoral experience abroad is preferred. Degree and Training Required PhD Duration 24 months Working time Full‑time Weekly working hours: 38h30 Annual leave and RTT (reduction of working time) Contract staff: €2,895.57 gross/month with 0–2 years of experience, or €3,287.45 gross/month with 2–4 years of experience. Apply now Fill out the form below to apply for this position. #J-18808-Ljbffr