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We have 48 Data Analysis (statistical) PhD Projects, Programmes & Scholarships

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Data Analysis (statistical) PhD Projects, Programmes & Scholarships

We have 48 Data Analysis (statistical) PhD Projects, Programmes & Scholarships

New frontiers in extreme data analysis

  Research Group: Data Science, Statistics & Probability
The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing in September 2024. . Read more

Statistical inference for epidemics models

Mathematical models have been established as an important tool for capturing the features that drive the spread of a disease, predicting the progression of an epidemic and guiding the development of effective control strategies to prevent potential outbreaks. Read more

Novel causal models for multivariate functional data

  Research Group: Data Science, Statistics & Probability
The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing in September 2024. . Read more

Robust Computational Methods for High-Dimensional Imaging

This project aims to develop new computational algorithms to optimize the acquisition and processing of single-photon data and enable fast imaging in extreme conditions using statistical and learning based approaches.   The project is funded for 3.5 years for international students and a ~£17K annual stipend. Read more

Investigating the genetic basis of immunological overlap between inflammatory diseases

Genetic studies have identified numerous variants within the human genome associated with susceptibility to common complex inflammatory diseases, such as rheumatoid arthritis (RA) and ulcerative colitis (UC). Read more

Distributed Sensing in Complex Photonic Network Ensembles

Apply to pursue a PhD in the Optical Theory Group, led by Matthew Foreman, where you will explore optical and plasmonic properties of random complex networks and develop novel sensing algorithms. Read more

Characterisation of tissue microstructure from non-invasive MRI using Machine Learning

The characterisation of biological tissue microstructure in vivo and non-invasively is of outmost interest in science. If successful, it could reveal unique insights into biological processes, including aging and cancer. Read more

Bayesian Deep Learning for cosmology with Euclid

This project will focus on the combination of cutting-edge Deep Learning and statistical methods to enable cosmological inference from next-generation facilities such as the European Space Agency’s Euclid mission. Read more

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