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an expert in the use of advanced statistical inference and machine learning methods for the analysis of omics datasets. You will work with a team of data scientists in Manchester and Oxford to create tissue
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mathematical biology, with a focus on analyzing image-based and time-series biological data through mathematical, statistical, and machine learning approaches. The role is designed for a researcher with
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work has been the use of statistical methods for the analyses of high-dimensional data and machine-learning approaches to elucidate correlates of natural and vaccine-mediated immunity in HIV
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databases containing spectral, chemical, mineralogical, and cartographic data of lunar samples. The role involves using Geographic Information Systems (GIS) such as QGIS and applying machine learning
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empirical and numerical methods. Physics-based learning could enhance model quality and generalisation by providing a physical foundation using synthetic data from these methods. * Developing machine learning
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SEM, LCA, latent variable models, time-series analysis, multi-level models, power analysis, and/or multiple imputation for missing data. Knowledge of machine learning methods, tools, and software
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interpretable machine learning, System integration implementation, Test environment configuration, Validation and stress testing, Deployment and configuration in test environments, Component restructuring, review
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, digital twins, and machine learning into process systems of industrial and societal relevance. Furthermore, we expect research proposals to align closely with the UN Sustainable Development Goals and to
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Geoscientist for developing and integrating large-scale 3D geological models of the Swiss Alps
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research team as a Research Engineer. The successful candidate will support ongoing research initiatives by applying advanced machine learning, NLP, and large language models (LLMs) to develop next