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markov PhD Projects, Programs & Scholarships

We have 13 markov PhD Projects, Programs & Scholarships

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Showing 1 to 10 of 13
  Stochastic processes in Health & Disease
University of Leeds School of Mathematics
  Dr M Lopez-Garcia
Applications accepted all year round
During the last years, increasing efforts are being devoted to better understanding a wide range of processes arising in Health & Disease.
Details
Type/Funding
  Two-stream Machine Learning Architecture based on Deep Learning and HMM for Person Recognition in Images/Videos
Kingston University Faculty of Science, Engineering and Computing
  Dr JC Nebel
Applications accepted all year round
The development of deep learning CNN architectures has led to remarkable progress in the field of computer vision. As a consequence, successful systems are now available for real world applications in a variety of areas including visual surveillance, sports analysis, gaming and security.
Details
Type/Funding
  Stochastic Multiscale Model of Evolutionary Competition of Molecules
University of Birmingham School of Mathematics
  Dr F Spill
Application Deadline: 31 January 2019
Oligonucleotides are not only the careers of genetic information. They can also form complex 3D structures with diverse chemical properties.
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
  Dynamical Redesign of Biomolecular Networks
King’s College London Department of Chemistry
  Dr E Rosta
Application Deadline: 26 March 2019
Project Description. We will develop novel theoretical frameworks [1] using machine learning approaches to address catalytic efficiency and to establish molecular design principles to key design problems for new bio-inspired nanocatalysts.
Details
Type/Funding
  Applying Lean Techniques to Patient Flow using Stochastic Modelling
Manchester Metropolitan University Faculty of Science and Engineering
  Dr M Latif
Applications accepted all year round
Reference Number. ML-2018-PhD-1. Project Summary. This research project explores the use and development of an integrated simulation model for the study of patient flow in hospitals and its dynamic effects on staffing, patients, and resources.
Details
Type/Funding
  Ion channel gating kinetics and structure implication for drug delivery
University of Bradford Faculty of Life Sciences
  Research Group: Chemistry and Biosciences
  Dr L Shang, Dr Z Hughes
Applications accepted all year round
Ion channels are proteins which sit in the membrane of every cell in the body and control the flow of positively charged ions such as sodium and potassium into and out of the cell.
Details
Type/Funding
  Modelling seismicity as a spatio-temporal point process using inlabru
University of Edinburgh School of Geosciences
  Dr M Naylor, Prof F Lindgren, Prof I Main
Application Deadline: 8 February 2019
BACKGROUND. This PhD is funded through the ‘RISE’ project as part of the Horizon 2020 program. Towards operational forecasting of earthquakes and early warning capacity for more resilient societies.
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
  Response of ringed seal populations to environmental change in the Canadian Arctic
University of Liverpool School of Environmental Sciences
  Dr R Jeffreys, Dr C Mahaffey, Dr SC Smout, Dr S Ferguson
Application Deadline: 23 January 2019
Introduction. The Arctic Ocean is undergoing unprecedented rates of environmental change, warming twice as fast as the global average (Hoegh-Guldberg and Bruno, 2010).
Details
Type/Funding
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