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Job Description We invite applications from highly motivated and talented researchers for a 2-year postdoctoral position in advanced skin models, cellular immunology, and spatial transcriptomics
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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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will use a combination of scRNAseq, spatial transcriptomics, and highly-multiplexed imaging to understand how human macrophages respond to the early stages of cancer development. They will be a part of
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spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable. The position offers an extraordinary team-based science environment with opportunities
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of high-dimensional data (e.g., single-cell RNA-seq, phylogenetics, spatial data) Experience in R or Python Application instructions: Please send a CV, a brief cover letter describing your research
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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a spatially explicit predictive model for Everglades vegetation dynamics in response to major drivers. The major objectives are to explore the distribution models that discriminate among prairie and
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, CSF) and/or advanced workflows such as spatial proteomics is highly desirable Strong collaborative spirit and working in interdisciplinary environments Excellent written and verbal communication skills
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that researcher ineligible for appointment at a similar level in another Irish HEI Researcher Career Development Framework | Irish Universities Association Project Title: Exploiting the spatial actions of metabolic
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches