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The successful candidate will join the Climate Physics team at ENS de Lyon (https://climatephysics-ensl.fr/ ), which currently consists of 5 permanent researchers, 7 PhD students and 2 postdoctoral researchers. We
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), within the ATLAS group. The PhD student will join a large-scale international collaboration and participate in the activities of the ATLAS experiment at CERN. The work will focus on the analysis of data
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language processing that address concrete problems and are both theoretically rigorous and interpretable. The PhD is funded by the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments
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web and linking source populations to the underlying halo and galaxy distribution; developing SBI pipelines for Fermi-LAT data, first standalone and then jointly with LSS. Qualifications. A PhD in
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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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acquire in the course of the PhD skills in live microscopy, experimental neurobiology, genetics and behavioural work. The student will receive mentoring and have the chance to guide the research and
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the molecular identity and function of specialised skin cells that become remodelled above the olfactory placode, and to determine how they acquire the properties required for orifice formation. The project will
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning
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remains open for the later stages of the PhD. During this PhD, the student will acquire highly valued skills in climate modeling, climate simulation analysis, and will contribute to expand the knowledge