Publisher
source

University Of Strathclyde

Funded PhD in Novel Time Series Machine Learning Methodology for High-Dimensional Data University of Strathclyde in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD project for students worldwide. The post indicates funding is provided, but it does not specify stipend amount, tuition coverage, or other financial details.

Deadline

Sep 30, 2026

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Country

United Kingdom

University

University Of Strathclyde

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Keywords

Computer Science
Machine Learning
Environmental Science
Deep Learning
Mathematics
Forecasting
Salud Pública
Bayesian Statistics
Anomaly Detection
Quantile Regression
Economics
High-dimensional Data
Statistics
Data Imputation

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About this position

Funded PhD opportunity at the University of Strathclyde in Novel Time Series Machine Learning Methodology for High-Dimensional Data.

This project sits in the Department of Mathematics & Statistics and focuses on developing new time series machine learning methods for high-dimensional data, with emphasis on missing data imputation, forecasting, anomaly detection, and probabilistic uncertainty quantification. The research combines statistical modelling and modern AI, including state-space models, Markov regime-switching networks, factor models, deep learning, temporal convolutional networks, transformers, Bayesian inference, and quantile regression.

Application areas include financial forecasting and risk modelling, public health monitoring, and environmental trend analysis such as air and water pollution across regions. The project aims to produce publishable research, open-source time series AI models, and deployment-ready prototypes for selected applications.

Supervisors listed are Dr Jiazhu Pan and Prof Ke Chen at the University of Strathclyde in Glasgow, United Kingdom.

This is a funded PhD project open to students worldwide. The post does not specify stipend amount, tuition coverage, or other financial details.

To apply, register your interest on the FindAPhD project page and submit the enquiry form. The university will respond directly after you send your details and question.

Funding details

Funded PhD project for students worldwide. The post indicates funding is provided, but it does not specify stipend amount, tuition coverage, or other financial details.

What's required

Applicants should be interested in time series machine learning, high-dimensional data analysis, forecasting, anomaly detection, and missing data imputation. The project is suitable for candidates with a strong background in statistics, mathematics, computer science, or related quantitative fields; the post does not specify additional formal requirements such as GPA or language tests.

How to apply

Register your interest through the FindAPhD enquiry form on the project page. The university will respond directly after you submit your details and question.

More information can be found here

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