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(preferably in R and/or Python). b) Preferential factors: Familiarity with spatial data analysis and/or Machine Learning methods will be valued. Workplan and objectives to be achieved: The work plan aims
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to high-dimensional omics datasets. Familiarity with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly
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-layer techniques (preferred/an asset, intermediate level). Proficiency in Python for scripting, data analysis, and automation (advanced proficiency required). Website for additional job details https
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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patient samples with advanced immune profiling approaches, including single-cell genomics, TCR repertoire analysis, spatial technologies, and functional immune assays. A major focus of the lab is to define
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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property that can be exploited to reduce the modal analysis to a single unit cell, i.e. the elementary pattern forming the lattice. Bloch theory provides a classical framework for investigating wave
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related to staff position within a Research Infrastructure? No Offer Description This research aims to investigate the mechanisms that control the spatial and temporal variation of soil organic carbon (SOC
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simulations. To elucidate the amplification mechanisms underlying the experimentally observed transition, the authors conducted a resolvent analysis, providing new insights into the subcritical amplification
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process, modification of the microenvironment components, and integration with state-of-the-art research technologies such as high- and super-resolution microscopy, quantitative image analysis, spatial