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), National Animal Disease Center, Virus and Prion Research Unit, located in Ames, Iowa. For an introduction to the Flu crew at the National Animal Disease Center, please see: https://youtu.be/kOJy8tFTuiI About
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· Demonstrable problem-solving skills · Ability to propose and apply novel (literature based) and innovative ideas for solving a problem Desirable · Knowledge of Bayesian uncertainty techniques
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Statistical Analysis Plan guidance (APT-SAP)’ project (https://sheffield.ac.uk/ctru/current-trials/apt-sap ). Provide high-quality statistical advice and support to multidisciplinary research projects within
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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
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, Applied Machine Learning, Neural Networks and Deep Learning as well as Machine Learning for AI and Data Science and Bayesian Theory and Data Analysis. We are looking for an associate able collectively
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-country survey datasets for comparative analysis. Conceptualize and refine a theoretical framework integrating intersectionality and stigma processes. Develop and code a Bayesian meta-regression to pool and
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forecasting. Familiarity with ensemble methods, Bayesian approaches, and uncertainty estimation. Experience with large-scale or messy real-world data (structured and/or unstructured). Interest in or experience
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(e.g., Bayesian inference, deep learning), ideally connected to spatial omics, and experience with frameworks like PyTorch, Keras, Pyro, or TensorFlow Application process: Interested candidates should
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Engineering (IMSE) at The University of Texas at El Paso (UTEP) https://www.utep.edu/engineering/imse/ is a dynamic department within the College of Engineering. The department offers one undergraduate degree
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restoration ecology (see https://www.slu.se/en/about-slu/organisation/departments/department-of-wildlife-fish-and-environmental-studies/ ). The department has many international employees and well-established