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Field
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modelling and spatial ecology project focused on urban Singapore. Key Responsibilities: The Research Fellow will develop species distribution models, multi-species occupancy models, biodiversity indicators
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environment data for Singapore from government agencies and open sources, using GIS software (i.e. QGIS), R, and Python. Undertake 2D and 3D geospatial modelling and analysis. Apply spatial and statistical
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and support all aspects of the research project. Carry out algorithm development and data analysis, including (but not limited to) single-cell and bulk transcriptomics, spatial omics, proteomics, and
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resource options, including cross-sector co-location. Conduct geospatial and data science analysis supporting site suitability, resource constraint mapping, scenario planning, and the COMPASS interactive
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on understanding the earliest stages of high-grade serous ovarian cancer (HGSOC) by integrating spatial multi-omic profiling with computational analysis to define how precancerous lesions evolve into invasive
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combines stem cell biology, spatial genomics, AI/ML, single-cell technologies and computational biology to study how mutant cell populations interact with their surrounding tissue environment during
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focus on advanced spatial and environmental data analysis. Based at Queen's University Belfast and working closely with Technological University Dublin, the Research Fellow will contribute to a dynamic
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support all aspects of the research project. Carry out algorithmic development and data analysis, including (but not limited to) single-cell and spatial transcriptomics. Implement state-of-the-art
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Participation Program offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and temporal scales, from the genome to the continent
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sample preparation, ion exchange column chemistry, low-level trace element geochemistry and/or high-precision radiogenic isotope analysis. Demonstrated experience in U-Th geochronology, MC-ICP-MS