PhD in Computational Systems Biology / Bioinformatics (M/F)

Description

Offer Description: As part of the PANDORA project, a PhD position is available at the Centre for Integrative Biology (CBI) in Toulouse, a joint CNRS–University of Toulouse unit dedicated to integrative biology at various scales. The successful candidate will join the Systems Biology group and will be supervised by Professor Anna NIARAKIS. Job description : Creation of a multi-scale predictive digital twin of the retina affected by age-related macular degeneration (AMD) (DC8) This PhD position forms part of the MSCA PANDORA doctoral network, which investigates the pathological mechanisms and optimisation of new drugs for age-related macular degeneration (AMD). Computational modelling enables researchers to integrate several types of biological data into a single framework, to test perturbations in silico, and to predict pathological mechanisms and responses to treatments before testing them in the laboratory. The PhD student will develop large-scale molecular interaction maps of retinal mechanisms linked to AMD and the complement system. They will convert these maps into executable Boolean models using the 'map-to-model' framework developed at the CNRS/UPS and INRIA, and then adapt the models to the specific conditions of AMD using omics data generated within the consortium. The models will then be integrated into an agent-based multi-scale model (ABM) to create a digital twin of the retina affected by AMD, simulating intercellular communication and tissue homeostasis. The digital twin will simulate the system disturbances studied experimentally at the network level: environmental stress conditions, different compositions of the extracellular matrix, gene inactivations and gain-of-function variants. The in silico predictions will be compared with in vitro data provided by the PANDORA project partners. Finally, the model will be used as part of a therapeutic reorientation strategy aimed at identifying and prioritising new therapeutic targets for AMD, which will then be passed on to the consortium for experimental validation. The host laboratory has recently developed a technology enabling Boolean models to be scaled up to a maximum of 1,000 biomolecules and ABM models to thousands of agents. The PhD student will build on these advances to create state-of-the-art, large-scale predictive models of AMD. We are looking for a highly motivated PhD student with a keen intellectual curiosity, possessing a solid background in computational or systems biology, bioinformatics or a related quantitative field.AMD is the most common cause of blindness in older people. Its pathological mechanisms are complex and not yet fully understood, making it a subject particularly well-suited to systems-level modelling. Skills/Qualifications : - A Master's degree in bioinformatics, computational or systems biology, biology with a strong quantitative focus, computer science, applied mathematics or a closely related field. - Programming experience (e.g. Python, R or similar). Solid knowledge of network biology, mathematical modelling and/or omics data analysis. - Excellent command of spoken and written English, as well as good presentation skills. - Strong motivation and a keen interest in pathological mechanisms and translational biomedical research. - Ability to work effectively both independently and as part of an interdisciplinary team. - Knowledge of cellular and molecular biology. Specific requirements: - Experience in logical/Boolean modelling, agent-based modelling or molecular interaction maps is a major asset. - Training in complement system biology, ocular biology or therapeutic reorientation is an asset. - Willingness to travel for secondments to partner institutions. - Ability to work independently. - Languages: ENGLISH Requirements: Research Field Chemistry Education Level Master Degree or equivalent Research Field Physics Education Level Master Degree or equivalent Research Field Biological sciences Education Level Master Degree or equivale

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Source

Source: euraxess.ec.europa.eu