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Field
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statistical and spatial analysis. Skills in conceptualization, design, and production of complex data visualizations to clearly communicate analytic findings. Strong critical thinking, analytical, problem
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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., proteomics, spatial transcriptomics, genomics, radiology). Postdoctoral applicants should have Ph.D., a solid publication record and strong professional references. The ideal candidate should have a
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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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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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Cancer Registry, as part of the national SEER registries. The postdoc fellow will work closely with statisticians, computer scientists, oncologists, and epidemiologists in the lab and other collaborating
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agricultural transformation and small-scale producers. Priority skills are proficiency with Stata, R and spatial mapping, and familiarity with the LSMS-ISA and other agricultural and spatial data in SSA and SA
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of Molecular and Spatial Biology of Skin headed by Thierry Nordmann MD-PhD, is providing a Postdoctoral Position (m/f/d). Project overview Inflammatory skin diseases affect a quarter of the population, yet our
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are as follows: Estimate the onshore technical and economic potential for CCUS in rural areas in Germany, the Netherlands and Norway. Gather high resolution spatial explicit data on (potential) CO2 sinks
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Pacific Institute for the Mathematical Sciences | Northern British Columbia Fort Nelson, British Columbia | Canada | about 1 month ago
in the following areas but are not limited to: Structure-preserving spatial and/or temporal discretizations for differential equations Structure-preserving machine learning methods Applications