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to be awarded, a PhD degree or equivalent in biochemistry, cell or molecular biology, genetics or a related discipline. We are seeking highly motivated applicants with practical experience in
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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communication skills in English. Strong skills in programming and data analysis. Track record of scientific publications in international peer-reviewed journals. Meritorious qualifications include: Experience
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data and clinical information. Applicants must hold (or be close to completing) a PhD in a relevant field and have expertise in modern computer vision and AI research. Experience with biomedical data
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experimental and theoretical approaches. Requirements: Well-documented expertise in any of the following areas: next-generation sequencing data analysis (singe cell and spatial sequencing). PhD in
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microorganisms, and developing of spectral collection and analysis protocols that will allow this biochemical data to be effectively used to support optical microscopy-based deep-learning algorithms for species
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. The overall aim of this project is to address these challenges by: Developing new data-driven and physics-based models of battery behaviour. Designing advanced BMS algorithms for real-time monitoring and
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Department of Ecology We are looking for a postdoc/researcher to develop and implement tools for analysis of output from Bayesian inference under phylogenetic models About the position A postdoc
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-unique CO2 experiments, cutting-edge NMR spectroscopy and isotopomer analysis (doi: 10.1111/nph.20358). Two postdocs will work together to conduct plant ecophysiology experiments, and to analyze samples by
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experiments, samples from world-unique CO2 experiments, cutting-edge NMR spectroscopy and isotopomer analysis (doi 10.1111/nph.20358). Two postdocs will work together to conduct plant ecophysiology experiments