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Field
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rooms are optimised for listening tests on loudspeakers to BS 6840-13 / IEC 268-13, and is equipped with state-of-the-art multi-channel spatial audio systems such as ITU standard layouts and Ambisonic
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“Enhancing Machine Learning Approaches for Spatially Dependent Data in Fisheries and Environmental Research” (CMAT, University of Minho), reference 2024.15617.PEX, financed by national funds through
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develop an industry-funded soil health framework for Australian agricultural production systems. The CERC Fellow will be a broad soil systems thinker and have a strong interest in using spatial approaches
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surrounding building such an experimental toolkit; from the ultrafast optics to the spatial resolution and statistical data analysis. Basic Qualifications PhD in Physics, Chemistry, Biology, Mathematics and
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collected during fieldwork. Experience with data analysis using software such as R for statistical analysis, including spatial statistics, 14C calibration, and site pattern recognition. Commitment
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specific focus on seasonal succession of host plants. Additionally, knowledge of agronomy, agricultural practices, and spatial technologies (e.g., global positioning systems – GPS) would be advantageous
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collected during fieldwork. Experience with data analysis using software such as R for statistical analysis, including spatial statistics, 14C calibration, and site pattern recognition. Commitment
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work with modern molecular profiling (e.g., single-cell and spatial transcriptomics, ATAC-seq) and quantitative imaging (including confocal microscopy). Start date is July 1st, 2026. Responsibilities
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genomics is considered an advantage Understanding metastatic potential and tumor immunobiology at the single cell and spatial level In this project we use all-things-omics, with short and long read
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availability within plant roots shapes development, physiology and adaptive responses. The overall aim of the project is to understand how internal oxygen landscapes arise in roots and how these spatial