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, calcium imaging, optogenetics and/or behavioural methods. The project is part of a broader research programme designed to use cross-species research to uncover mechanisms for memory in both health and
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of our research program is to understand the neural circuits that underlie cognitive and emotional behavioral decision-making. Many of our research projects are focused on neuromodulatory circuits such as
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understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and upcoming AI methods to analyze the climate
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independent work but demands a comprehensive understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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of statistical techniques to ability interpret 16S rRNA data, including microbiome data. Good/strong organization skills; ability to multi-task, prioritize and meet deadlines. Must demonstrate attention to detail
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using R for statistical analysis and in statistical modeling. Sound working knowledge of unix shell, high performance compute clusters and git. Willingness to learn and use a scripting language (e.g
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deep shotgun sequencing data to profile the microbiome at the taxonomic and functional levels and applying statistical analyses to large datasets to identify (ideally, genetic) factors affecting
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classes in the graduate and undergraduate curricula and/or similar classes, either in an in-person or online modality: ● Quantitative and Psychometric Methods ● Multivariate Statistics ● Measurement
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information science, and applied social science research. This position is well-suited for someone interested in research design and the application of geographic principles and methods to policy analysis and