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bayesian PhD Projects, Programs & Scholarships

We have 51 bayesian PhD Projects, Programs & Scholarships

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  PhD Studentship in Bayesian Artificial Intelligence for Decision Making Under Uncertainty
Queen Mary University of London School of Electronic Engineering and Computer Science
  Dr A Constantinou
Application Deadline: 15 March 2019
Do you enjoy working with probabilities, data, and algorithms? Are you interested in the theory of causality? Do you want to improve the methods we use…
Details
Type/Funding
  Approximate Bayesian methods for scalable inference
Heriot-Watt University School of Engineering & Physical Sciences
  Dr Y Altmann
Application Deadline: 8 February 2019
This project consists of investigating new approximate Bayesian methods for fast and robust estimation in high dimensional problem.
Details
Type/Funding
  Bayesian Uncertainty Quantification for Clustering Problems
Queen Mary University of London School of Mathematical Sciences
  Research Group: Statistics
  Dr W Yoo, Dr S Liverani
Applications accepted all year round
The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2019 for students seeking funding, or at any point in the academic year for self-funded students.
Details
Type/Funding
  Locally-adaptive Bayesian modelling for medical image reconstruction
University of Leeds School of Mathematics
  Dr R.G Aykroyd
Applications accepted all year round
The use of medical imaging techniques are critical in the early diagnosis and treatment of many serious conditions. Over the past 20-30 years there have been major advances in imaging speed and resolution along with equally dramatic decreases in cost.
Details
Type/Funding
  PhD Studentship Opportunity in Uncertainty quantification in high-dimensional spaces with Bayesian deep learning
University of Surrey Faculty of Engineering and Physical Sciences
  Research Group: Nature Inspired Computing and Engineering
  Dr Y Li
Applications accepted all year round
The Nature Inspired Computing and Engineering (NICE) Research Group in the Department of Computer Science at the University of Surrey invites applications for a funded studentship in Machine Learning.
Details
Type/Funding
  Bayesian Inference for Scanning Probe Microscopy Forcefield Inversion
University of Manchester School of Mathematics
  Prof K Law
Applications accepted all year round
The problem of fully Bayesian force-field inversion given observations from scanning probe microscopy will be considered here. The forward model is given by a simple harmonic oscillator perturbed by the nonlinear force-field, which is parametrized by a linear interpolant or expansion in some other basis.
Details
Type/Funding
  Bayesian identifiability for log-linear models.
University of St Andrews School of Mathematics and Statistics
  Research Group: Division of Statistics
  Dr M Papathomas
Applications accepted all year round
Log-linear modelling is the standard approach for investigating the full joint dependence structure between categorical variables such as phenotypes and SNPs.
Details
Type/Funding
  Bayesian calibration methods for cardiac electrophysiology models
Queen Mary University of London School of Mathematical Sciences
  Research Group: Statistics
  Dr S Liverani
Applications accepted all year round
The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2019 for students seeking funding, or at any point in the academic year for self-funded students.
Details
Type/Funding
  Computational Imaging: Improving the Acquisition and Processing of Single-Photon Data
Heriot-Watt University School of Engineering & Physical Sciences
  Dr AH Halimi, Prof S McLaughlin
Applications accepted all year round
Recent technological innovations, eg detection and acquisition hardware, have pushed sparse-photon imaging to the fore in a variety of applications including 3D Lidar imaging and microscopy.
Details
Type/Funding
  Weather Generator for Future Climates
Newcastle University Faculty of Science, Agriculture and Engineering
  Prof C Kilsby
Application Deadline: 31 January 2019
This project is part of the ONE Planet DTP. Find out more here. https://research.ncl.ac.uk/one-planet/. Recent climate model outputs are probabilistic, and provide change factors rather than explicit time series or extreme event frequencies, which are usuallly required for impacts studies e.g.
Details
Type/Funding
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