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set a course for the future – a future that you can help to shape. PhD Position: Spatial Omics Meets Neurodegeneration — Mapping Therapeutic Targets in Charcot-Marie-Tooth Neuropathy Position How do you
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of differences in the workplace Preferred Qualifications: Experience conducting advanced spatial statistical analyses related to environmental health risks (hotspot analyses, spatial regression analyses) Written
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Mathematics and Mathematical Statistics is opening a PhD position in spatial statistics
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visualization of spatial data; environmental geospatial modeling, remote sensing and spatial statistics; relational database concepts; identification of spatial temporal turbidity patterns in coastal waters using
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in Data Science and Statistics with expertise in the application of data science to spatial and space-time data from problems throughout the geosciences. The Department of Applied Mathematics and
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ovarian cancer. The laboratory has about 15 members that use cutting-edge methods, including spatial proteomics, spatial metabolomics, spatial transcriptomics, 3D organotypic cultures of human tissue, in
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on the development of a virtual tissue model bridging cell-cell communication and gene-gene interactions by exploiting spatial transcriptomics data and network-theoretic approaches. Contract start date : May 1st 2026
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 7 hours ago
), financed by national funds through FCT Workplan: The main objective of the fellowship will be to study the effects of heterogeneity in spatially-structured or host-structured multi-species models governed by
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting