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in nematodes. Much of our work now focuses on the evolution of egg-laying behaviour and the transitions to viviparity. In parallel, we are also interested in characterizing the natural history, ecology
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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained
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the framework of the PEPR Sous-Sol project ORGMET conducted by a consortium of four French laboratories GET, INEEL/ESRF, LFCR and IPREM (https://www.soussol-bien-commun.fr/fr/appel-projets-2024/orgmet
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description: We are seeking a postdoctoral researcher with solid expertise in device physics modelling, compact model development, and/or circuit simulation. The successful candidate will: • Develop physical
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conditions such as cancer, yet the underlying mechanisms remain poorly understood. Understanding how disruptions in these processes contribute to cancer development and cell fate decisions is a central
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). The successful candidate will contribute to the development, optimization, and application of PET-CT imaging protocols for small animal models included in quantitative multi-imaging modalities. Responsibilities
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, optimisation of chromatographic conditions, development of a comprehensive standards database) and will perform metabolomics studies in human, cellular and animal samples. He/She will contribute
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of wood formation (CEMACam project). - main mission: The candidate will be tasked with continuing the development of a wood formation simulation model initiated during the project. This 'vertex' model
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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for experimental work, analysis (NMR, HPLC), and writing scientific reports, and will benefit from an international research environment. Development of original methodologies in order to tackle key synthetic