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Field
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uniquely accessible human fetal tissue from the Scottish Advanced Fetal Research Study (SAFeR), advanced single-cell genomics, proteomics, spatial imaging and ex vivo human tissue models, the programme will
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insights, and applying appropriate AI models for geospatial analysis based on the integrated data. This role is part of the project: Decision-support-tools for Spatial Planning and Cumulative Effects
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) Center of Excellence Research Participation Program offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and temporal
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the sensing payload · Prepare clean, georeferenced, time-synchronised, and well-documented datasets · Support quality assurance and quality control of collected data, and assist with analysis and
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-seq, ATAC-seq, ChIP-seq, spatial transcriptomics and single-cell data. Familiarity with data integration frameworks, predictive modeling, and network analysis. Experience with cloud computing
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, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data. Independently carry out computational and bioinformatics analysis for large-scale spatial and single-cell omics as well as next
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on participation in animal study design, preparation, and execution. Post-collection processing and analysis of animal specimens may also be performed through laboratory assays (e.g. nucleic acid extractions, RT
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spatial analysis of heavy metal accumulation. Alongside shaping this research, you will actively share your discoveries through scientific publications and international presentations. Furthermore, you will
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an emphasis placed on participation in animal study preparation and execution. Post-collection processing and analysis of animal specimens may also be performed through laboratory assays, along with
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research. Key Responsibilities: Develop, implement, and optimize machine learning/deep learning models for digital pathology image analysis Analyze large-scale histopathology, omics, and clinical datasets