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to air pollution in the future, and planning further policy changes. This PhD project will develop statistical modelling frameworks that are able to handle large-scale, complex, and correlated time series
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seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis
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exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural
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drives tumour development, childhood cancers lack the extended time frame needed to accumulate the mutations required for tumorigenesis by those routes. Therefore, endogenous mutagenic processes are a
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-organising reaction networks and the emergent complexity in such systems form powerful reservoir computers capable of non-linear classification, times-series prediction and forecasting, on a par or even
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vast amounts of short, irregular biomedical time-series data, including physiological signals, lab results, and interventions. These data hold great potential for supporting high-stakes, complex decision
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to air pollution in the future, and planning further policy changes. This PhD project will develop statistical modelling frameworks that are able to handle large-scale, complex, and correlated time series
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or as soon as possible thereafter. For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £20,780 for 3.5 years full-time, or pro rata for part-time
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, Skills and Experience • You will have substantial technical experience in time series analysis, ideally either in neurophysiology data or wearable sensor data • You will have experience of at least
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering