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We have 104 Applied Statistics PhD Projects, Programmes & Scholarships for Self-funded Students
Applied Statistics PhD Projects, Programmes & Scholarships for Self-funded Students
We have 104 Applied Statistics PhD Projects, Programmes & Scholarships for Self-funded Students
PhD Studentship in “Applications of harmonic analysis in probability and equidistribution theory”
Classical Fourier analysis as well as abstract harmonic analysis on groups and manifolds provide powerful tools in a large number of areas including number theory, probability theory, equidistribution theory and optimal transport. Read more
(BBSRC NWD) Leveraging machine learning to uncover multimorbidity clusters in rheumatoid arthritis
Chronic inflammatory diseases such as rheumatoid arthritis (RA) are potentially life-ruining. Read more
SparseHybrids: Sparse designs, statistical machinery and breeding tools for leveraging heterosis in plants and animals
Summary. Unique PhD project in quantitative genetics, biometrics and selective breeding with leading academic and industry experts from UK, Europe and Australia. Read more
BBSRC NWD CASE: Unravelling the Molecular Mechanisms of Bacterial Interspecies Interactions in the Skin Microbiome
Human skin is a nutrient-scarce environment colonised by many different microorganisms forming intricate microbial communities. Alterations of the skin microbiome composition are associated with different skin conditions (e.g., acne, body odour and atopic dermatitis). Read more
Quantifying the physical and tactical demands of wheelchair tennis on different court surfaces (Ref: SSEHS/AFP25)
This project will seek to compare the physical and tactical demands of wheelchair tennis on different court surfaces (hard, clay and grass). Read more
Performance of supercritical CO2 power generation systems - PhD studentship
Due to unique properties of supercritical CO2 (sCO2), power generation systems using sCO2 as working fluid have many advantages over their counterparts, such as gas turbines and steam turbine power plants. Read more
PhD in Evaluating the Influence of Tangible 3D Printed Replicas on the Museum Experience
The University of Warwick, and Oxford University Museum of Natural History, are pleased to announce the availability of a fully-funded four-year (full-time) doctoral grant under the AHRC’s Collaborative Doctoral Partnership Scheme. Read more
Efficient design of high-throughput molecular studies.
A typical experiment might consist of taking one sample from each of 100 patients, measuring many molecular properties, and then performing an analysis. Read more
Topics arising from the UK Prostate ICGC (International Cancer Genome Consortium) project.
The UK Prostate ICGC project has generated many data on a cohort of men with the prostate cancer that have the following notable features. Read more
Stochastic simulation, analysis, and inference for non-linear dynamical systems
This project aims to create a new modelling framework for describing systems that exhibit non-linear dynamics, such as oscillations or multiplicity of equilibria. Read more
Integrating multivariate modelling with stochastic optimization to plan firebreaks
Research Group:
Division of Statistics
Wildfires are a well-known matter of concern worldwide. In particular, Portugal has recently seen a total burn area severe increase, attaining the unsettling value of 110097 ha, in 2022. Read more
Inferring Events from Phylogenetic Analysis of Eyewitness Testimony in the Historical and Forensic Record
This project will consider if we can use phylogenetic analysis to correct for imperfections in eyewitness testimony. Eyewitness testimony from events with multiple witnesses is often inconsistent and sometime contradictory. Read more
Improved survival analyses in molecular cancer studies
Improved survival (whether this is literal survival, time to a change in symptoms, or time to disease progression) is a key outcome in cancer research. Read more
Identifying complex spatio-temporal biomarkers of brain diseases
Bayesian models today are providing the tools to explore the complexity of brain architecture. Therefore, there is a crucial need for leading researchers with an in-depth comprehension of the current challenges in neuroscience and the quantitative skills to develop cutting-edge solutions. Read more
High-dimensional functional time series modelling of environmental datasets
Research Group:
Division of Statistics
In a dynamic time-series model, selecting the appropriate lag order is crucial for understanding the predictive relationships among variables and generating accurate forecasts. Read more