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Postdoctoral Researcher in Synthetic Organic Chemistry and Photochemistry, IBMM, Montpellier, France
heterogeneity and detailed architecture of human tissues yet. This project aims to develop a selective photoactivatable crosslinking chemistry that will enable the fabrication of heterogenous living constructs
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computational approaches to biological systems. Its core activity is the development of deep learning methods for protein design and optimization, with applications in biology and medicine. - activities: We
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at understanding how chromatin acetylation affects nucleocytoplasmic transport. - main mission: Formulate and develop a scientific question Select, adapt, develop and implement experimental approaches
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de Rham" methods, the main feature of which is to reproduce subtle mathematical properties expressed by Hilbert complexes at the discrete level. The developments envisaged within the NEMESIS project
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IATE partners. Supervise the collection and processing of samples (fish feces, exposed microplastics). Develop and optimize enzymatic and chemical cleaning protocols for samples. Perform advanced polymer
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(EMF) plays a key role in understanding the evolution of the planet, its climate, and its habitability over the past 4.5 billion years (Shahar et al. 2019). Paleomagnetism, which allows us to study past
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. Main mission : To develop and integrate a robotic platform for multiscale biomechanical testing of murine cartilage and intervertebral discs under biomimetic loading conditions, coupled with advanced
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optimize the UV micro-photoluminescence setup. Perform optical and cryogenic tests. Develop the software for control of the instruments and data acquisition based on PyModAq, Where to apply E-mail
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the hydrogeology of volcanic and basement aquifers. - main mission: The recruited researcher will contribute to the development and implementation of numerical flow and transport models to improve the understanding
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functioning will be supported by several EU projects (participation to congress etc..). - main mission: He/she will develop a new generation of predictive models incorporating abundance distribution across size