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Data Analysis (self) PhD Projects, Programs & Scholarships

We have 180 Data Analysis (self) PhD Projects, Programs & Scholarships

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  Self-organized collective patterns on graphs (ESR 3)
  Prof M Hutt
Application Deadline: 31 January 2020

Funding Type

PhD Type

Over the last few years, diverse studies have established that many forms of dynamics self-organize on networks to give rise to large-scale collective patterns.
  Internet of Things Infrastructure for Sustainable Wildlife Conservation (Self-Funded Students Only)
  Research Group: Complex Systems
  Prof O F Rana, Dr C Perera
Applications accepted all year round

Funding Type

PhD Type

This project will investigate the design and development of an end-to-end, distributed, Internet of Things (IoT) infrastructure to support sustainable wildlife conservation.
  Adaptive self-learning vision systems
  Dr P Kinnell, Dr N Lohse, Dr A Soltoggio
Applications accepted all year round

Funding Type

PhD Type

Many computer vision systems make use of artificial neural networks to undertake complex image analysis tasks, such as locating objects in a clutter scene.
  Data analysis for digital-entrepreneurship/self-employment (Application Ref: SF19/EE/CIS/ANWAR)
  Dr MN Anwar, Dr A Ali
Applications accepted all year round

Funding Type

PhD Type

This age of big data gives a great opportunity to turn large-size datasets with high-velocity and diverse structures into real advantage in many fields, such as health, economics, education and disaster prevention.
  Personalised content exploration engine to support self-management of multiple chronic conditions
  Research Group: Applied Computing
  Dr D Thakker
Applications accepted all year round

Funding Type

PhD Type

The self-management model in health aims to empower a person to be more active participant in his or her own care [1]. Involving patients actively in their own care is critical for controlling disease management costs associated with monitoring and assessment.
  Edge Computing for Internet of Things (Self-Funded Students Only)
  Research Group: Complex Systems
  Prof O F Rana, Dr C Perera
Applications accepted all year round

Funding Type

PhD Type

This project has two different research themes. (1) Edge Computing; (2) Data Science. (1) Edge Computing is the notion of performing computation close to the data generation source, by significantly reducing data communication latency and ensuring that private data is maintained closer to the data generation source.
  Privacy and Security by Design for Internet of Things (Self-Funded Students Only)
  Research Group: Complex Systems
  Prof O F Rana, Dr C Perera
Applications accepted all year round

Funding Type

PhD Type

The design process for Internet of Things (IoT) applications is more complicated than for desktop, mobile, or web-based platforms.
  Semantic Web Technologies and Linked Data for Internet of Things (Self-Funded Only)
  Research Group: Complex Systems
  Prof O F Rana, Dr C Perera
Applications accepted all year round

Funding Type

PhD Type

The ultimate goal of Semantic Web is to make the machine to understand the Internet data. To enable the encoding of semantics with the data, well-known technologies are RDF (Resource Description Framework) and OWL(Web Ontology Language).
  Digital manikins as a novel tool to measure self-reported pain in large-scale research studies
  Dr S Van der Veer, Prof W Dixon
Applications accepted all year round

Funding Type

PhD Type

Moderate to severe pain affects 1 in 5 adults. It is among the most prominent symptoms of musculoskeletal disease, and substantially affects the quality of life of people suffering from it.
  Adaptive Service Composition Techniques and Algorithms for Internet of Things (Self-Funded Students Only)
  Research Group: Complex Systems
  Prof O F Rana, Dr C Perera
Applications accepted all year round

Funding Type

PhD Type

Service composition is a collection of services where, many smaller services are combined together to a larger service. Service composition is the problem of aggregating services in such a way that given (functional and not functional) requirements are satisfied.
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