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- Solid knowledge of existing literature in optimization and/or symbolic computation - Strong skills in programming with scientific and/or symbolic computing tools Website for additional job details https
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— an essential step for effective regeneration (Schaeffer et al., Neuron, 2023). A key aspect of our work is to understand how neurons regulate gene expression locally within axons through local ribosome supply
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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(cholesterol esters) and proteins; in particular, the person recruited will be responsible for optimizing the parameters for neutral lipids. • Develop and implement new methodologies for analyzing molecular
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characterization of nanocomposite films and interfaces. Interpret the experimental results. Highlight these results in relation to the work in the literature. Write scientific articles and communicate the results
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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proposed for improving the accuracy of medical diagnoses, identifying biomarkers and understanding glioma features in MRI data. The successful candidate will work in particular on : - Development of a pre
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on the development of materials and processes and is divided into two axes. The first axis aims to improve the most promising state of the art cell materials by optimizing their compositions, microstructures and
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to efficiently identify materials with optimal mechanical properties and controlled degradability. The primary task is to develop techniques for synthesizing degradable polymers and copolymers using ring-opening
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optimizations are still needed to adapt the translation of these mRNAs to the cell types of interest. As part of a collaboration with Chantal Pichon's team (University of Orleans), this project aims to use