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to quickly learn new skills Ability to work independently and without significant supervision Excellent verbal and written communication skills Intermediate proficiency in Google Suite and Teams/MS Office
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software
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for disease transmission. Research activities will include: Collaborate with subject matter experts to learn about the development of analytical tools for assessing Highly Pathogenic Avian Influenza (HPAI
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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, development of complex data visualizations, and demonstrated skill in one or more of the following areas: machine learning, statistical analysis, natural language processing and text analysis; experience
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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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with epilepsy across multiple NHS hospitals. They are expected to have some experience working with NLP in general and LLMs in particular. They will also help to further develop machine learning models
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have exceptional resources to facilitate research including access to administrative, research, and computer support staff. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology
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working with NLP in general and LLMs in particular. They will also help to further develop machine learning models to predict clinical outcomes. Familiarity with current methods in this area is essential
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in several areas. These include, but are not limited to, Using MPS to identify new potential targets for future medical countermeasure development Learning development and characterization