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offshore wind development and/or marine sectors such as fisheries and aquaculture Experience with ecosystem services, integrated assessment approaches, or marine spatial planning Familiarity with policy
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research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for spatial population
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environments. The aim is to generate robust time-resolved data on the kinetics and spatial distribution of enamel demineralisation and remineralisation, and to support future reaction-diffusion modelling and
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, functional, spatial, and temporal aspects of engineering information. The research will investigate how such integrated representations can support consistency checking, automated reasoning, and the synthesis
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, protein, PTM, metabolites) in different resolutions (e.g. subject, tissue, single cell) with or without spatial features. Analyse large-scale omics datasets, interpret results, and generate biological
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for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required (Python/R, ML/stats
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: · Perform collaborative research with multiple faculty members at ARDMRI on projects involving genomics data analysis using single cell RNA-seq, CHIP-seq/ATAC-seq, spatial transcriptomics, HiC/HiCHIP, RIBO
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spatial transcriptomics to link molecular signatures with tissue architecture. Develop predictive models for disease diagnosis, prognosis, and therapeutic targeting. Experimental and Analytical Approaches
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imaging and microscopy methods, and perform computational data analysis. Previous experience in translational cancer biology or immunology, spatial biology, and microscopy are preferred but not required
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storm events. Martian aurora, investigating the spatial and temporal variability of auro-ral emissions using multispectral imaging and spectroscopic data from the Perse-verance rover (SuperCam, Mastcam-Z