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Field
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encourage all qualified candidates, regardless of background, to apply! Job description The candidate will work on large-scale data analysis of cancer transcriptomics data (bulk, single cell and spatial), and
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expected that the successful candidate will contribute to the computational analysis of multi-omic data that will be generated during the project. The candidate must hold or be near completion to a PhD/DPhil
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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, large-scale measurements that can be used to estimate surface variables of interest. In particular, radar data can nowadays be used to obtain maps of surface soil moisture at a high spatial resolution (a
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Minimum Qualifications - PhD in ecology, remote sensing, environmental sciences, or a related field - Strong quantitative skills, including ecological data analysis, statistical analysis and data management
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prostate cancer lethality derived from Visium spatial transcriptomics (https://youtu.be/YdzF0-PFXhc ; https://www.nature.com/articles/s41586-022-05023-2 ; ). About You You will have a PhD (or close
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prostate cancer lethality derived from Visium spatial transcriptomics (https://youtu.be/YdzF0-PFXhc ; https://www.nature.com/articles/s41586-022-05023-2 ;). About You You will have a PhD (or close
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tumor spatial biology via single cell spatial analysis of the tumor microenvironment. Projects aim to reveal molecular mechanisms of drug resistance based on intercellular and intracellular regulation
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), based at the Centre for Human Genetics, University of Oxford. The post aims to assist with the preparation and molecular characterisation of tumours using multi-omic analysis focusing principally
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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and