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artificial intelligence and mathematical modeling, to study behaviors affecting individuals with disabilities such as behavioral relapse and self-injurious behavior. This position does not require a background
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expertise in mathematics, biometry, bioinformatics and data science, together with agribusiness, actuarial science, geographical information systems, farming systems and plant pathology. We have strong
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the field of quantitative marine science, particularly stock assessment modelling or ecosystem modelling. We encourage you to apply if you have a major or minor in mathematics, statistics, computing
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Midlands Graduate School Doctoral Training Partnership | Warwick, England | United Kingdom | 3 months ago
quantitative techniques including descriptive and exploratory analyses of mobility; sequence and trajectory analysis of educational and employment pathways; and quasi-experimental methods to address selection
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enrolled in a Masters or PhD programme in the School of Environment or the Department of Mathematics. Business School A $5,000 Scholarship to support an international or domestic student enrolled in
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to augment classical spike train analysis methods particularly those developed by Prof. Grün and others for detecting synchronous spiking activity with AI-based enhancements. After profiling the classical
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on model behavior. We will divide our work into three thrusts: Thrust A: A first major objective will be to augment classical spike train analysis methods particularly those developed by Prof. Grün and
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studies and techniques, insect identification, and statistical analysis of ecological data. Opportunities to learn insect rearing and testing of vector competence for VSV will be available. The fellow will
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strongly motivated by practical challenges in the design and analysis of clinical trials, while also offering scope for methodological innovation and theoretical development. Key responsibilities will
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across subsets of neurons to low-dimensional manifolds of high-dimensional space of population neuronal firing rates. Thus neuronal experimental data are to be analyzed for both aspects by PCA analysis and