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University Of Strathclyde
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Fully Funded PhD in Novel Time Series Machine Learning for High-Dimensional Data at University of Strathclyde University of Strathclyde in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Sep 30, 2026
Country
United Kingdom
University
University Of Strathclyde

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About this position
Fully funded PhD opportunity at the University of Strathclyde in the Faculty of Science, Department of Mathematics & Statistics, Glasgow, Scotland, United Kingdom.
The project is titled Novel Time Series Machine Learning for High-Dimensional Data and focuses on research in Artificial Intelligence, Machine Learning, Statistics, and High-Dimensional Time Series Analysis. Core topics include high-dimensional time series forecasting, missing data imputation, transformer and deep learning models, anomaly detection, and probabilistic forecasting with uncertainty quantification. Applications are described across finance, healthcare, environmental monitoring, and evidence-based decision-making.
This is a fully funded PhD studentship. The post states that tuition fees are covered subject to university funding terms and that a stipend is provided in line with UK Research funding where applicable.
Eligibility is aimed at applicants with a Master’s degree in Artificial Intelligence, Machine Learning, Statistics, Data Science, Mathematics, Computer Science, Econometrics, or a related discipline. Strong programming, analytical, and research skills are preferred.
Supervision is by Dr. Jiazhu Pan (Principal Supervisor) and Prof. Ke Chen (Co-Supervisor). Research enquiries can be sent to [email protected] or [email protected].
The application deadline is 30 September 2026. Interested candidates should follow the university graduate research route and review the linked graduate research page for application details.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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