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Field
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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, clinical, structural bioinformatics data, which should be outlined in the CV Prior experience in large-scale data processing and statistics / machine learning is required Demonstrated skills and knowledge in
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(organelles such as chloroplast and protein complexes) in their cellular environment, cryo-electron tomography (cryo-ET) is becoming a pivotal imaging approach. Therefore, CEA Irig is recruiting a researcher to
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physics and biology. The institute also benefits from state-of-the-art core facilities, particularly in microscopy (Microscopy Rennes Imaging Center, MRic, https://microscopie.univ-rennes1.fr/ ). Rennes is
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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) / InP contact layer (200 nm) / Si substrate The objective of the project is to develop a plasma etching process for this multilayer stack, enabling selective etch stopping on the InP contact layer, which
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of wildtype and Bdf1-mutant C. albicans strains. The project will also involve developing high-resolution 3D X-ray imaging approaches to investigate morphotype-dependent changes in the nuclear and subcellular