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Data Analysis PhD Projects, Programs & Scholarships in Birmingham

We have 22 Data Analysis PhD Projects, Programs & Scholarships in Birmingham

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  Analysis of pathogen determinants recognized by the hypervariable immune receptor Dscam
  Dr M Soller
Applications accepted all year round
Background. To mount an immune response, host organisms must first recognize the pathogen with which they are infected. The first line of defense against pathogen infection in animals is provided through the innate immune response.
  Integrating omics, imaging and informatics to develop physiology-based kinetic (PBK) models for perturbation biology in an invertebrate model species
  Prof M Viant, Dr B Campos, Dr C Rivetti, Dr I Sorrell
Application Deadline: 4 February 2019
This exciting 4-year BBSRC iCASE PhD opportunity bridges the University of Birmingham’s (*) metabolomics team and Unilever’s Safety and Environmental Assurance Centre (SEAC), both having state-of-the-art facilities and renowned research programmes, thereby creating an excellent environment for this challenging yet impactful research project.
  Algorithms and software for structured Semidefinite Optimization problems
  Prof M Kocvara
Applications accepted all year round
This project is part of the HORIZON 2020 Marie Skłodowska-Curie Innovative Training Network "POEMA, Polynomial Optimization, Efficiency through Moments and Algebra", which is offering 15 PhD positions, starting from September 2019 (more about POEMA below and here https://easychair.org/cfp/POEMA-19-22).
  The effects of risk measurement variability on clinical decision-making
  Prof T Marshall
Applications accepted all year round
Clinical measurements are undertaken to diagnose patients and to determine eligibility for treatment. They are also undertaken to monitor response to treatment.
  Breaking Free with Artificial Intelligence: The Data Science of Digital Behaviour Intervention.
  Dr C Yau
Application Deadline: 22 January 2019
Using digital technology to improve health and care is now a priority focus for the UK National Health Service. New and maturing technological developments hold the potential to have a transformative effect on health service delivery.
  Dimension-free Structure-aware Data Analytics: From Theory to Practice
  Dr A Kaban
Application Deadline: 22 January 2019
High dimensional data comes with computational, statistical, inferential, geometric, and interpretational challenges in general. However, the inherent difficulty of these problems may vary hugely across problem instances and particular data sets.
  Extracting novel algorithms from Nature
  Dr G Bassel, Dr I Johnston
Application Deadline: 22 January 2019
The development of algorithms underpins the information processing age and data science. Creating novel algorithms capable for processing information under different conditions and scenarios provides opportunities to extend computation to new domains and under different conditions.
  Stochastic Differential Equations for Systems with Extreme Events
  Dr S Johnson, Dr F Spill
Application Deadline: 22 January 2019
A great many real-world phenomena which involve some degree of randomness can be described with stochastic differential equations (SDEs).
  Beyond success: predicting the likelihood of a case eventually contributing to a shift in case law
  Prof S Delacroix
Application Deadline: 22 January 2019
Uncertainty. whether it be developing tools to help communicate it in lay-professional encounters, tools that take into account human uncertainty (and the consequent need for continuing change in a legal system), or methods to flag up / explain uncertainty to professional (or public policy) users of data science tools.
  Communicating Uncertainty within professional applications
  Prof S Delacroix
Application Deadline: 22 January 2019
Uncertainty. whether it be developing tools to help communicate it in lay-professional encounters, tools that take into account human uncertainty (and the consequent need for continuing change in a legal system), or methods to flag up / explain uncertainty to professional (or public policy) users of data science tools.
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