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to root patterning. Integrate molecular and imaging data into a spatio-temporal developmental framework. Research environment and approaches The project is highly interdisciplinary. The successful candidate
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apply analytical workflows for high-throughput breath analysis, ensuring robust and reproducible data. Work closely with clinical and research partners to translate findings into practical screening
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molecular biology approaches, live cell imaging and the generation and analysis of multi-omics data sets. The successful candidate will be responsible for accurate and efficient data generation, data
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precision operation as well as carry out data collection, system evaluation and benchmarking analysis; (g) prepare high-quality research outputs, including journal articles, conference papers, technical
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track record of collecting data on animalbehaviour. Experience of statistical analysis. Evidence of publication record commensurate with stage of career. The ability to work closely with animals and
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genetic analysis Strong background in plant-microbe interactions, effector biology Affinity with plant phenotyping Strong communication skills, proven ability to lead experiments, analyze data, and publish
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analysis. Define genetically defined and non-defined PD, MSA, HSP, RED phenotypes. Re-analyse short read exome and genome data. Long-read DNA sequencing and analysis in select genetically negative families
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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in computational analysis of omic data-ability to perform statistics, data integration and bioinformatics Candidates who are nearing completion of their PhD may apply, but confirmation on awarded PhD
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to collection and processing of research samples. They will lead in study data collection, analysis and write-up, and will present results at local and national meetings. It is expected that they will contribute