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Information Science (web) PhD Projects, Programs & Scholarships

We have 29 Information Science (web) PhD Projects, Programs & Scholarships

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Showing 1 to 29 of 29
  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).
  Artificial Intelligence for the Future of SocietyCities
  Prof W Hall
Application Deadline: 8 August 2020

Funding Type

PhD Type

Supervisor. Professor Dame Wendy Hall. Co-supervisor. Professor Pauline Leonard. Project description.
  AIFS: Privacy and data security in hyperconnected urban communities
  Research Group: Web and Internet Science
  Prof W Hall
Application Deadline: 31 August 2020

Funding Type

PhD Type

Supervisor. Professor Wendy Hall. Co-supervisor Professor Pauline Leonard. Project description. The Web Science Institute is offering a PhD research project in AI for the Future of Society (AIFS) in collaboration with Fawley Waterside Ltd.
  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.
  Security threat intelligence
  Research Group: Cyber Security and Networking Research Group
  Dr A Winckles, Dr M Graham
Applications accepted all year round

Funding Type

PhD Type

Research Group. Cyber Security and Networking Research Group. https://www.anglia.ac.uk/science-and-technology/research/our-research-institutes-and-groups/cyber-security-and-networking-research-group.
  Deep-learning for semantic-based information extraction from natural language
  Research Group: Computing, Informatics and Applications Research Group
  Dr A Fatima, Dr C Luca
Applications accepted all year round

Funding Type

PhD Type

Research Group. Computing, Informatics and Applications Research Group. Proposed supervisory team. Dr Arooj Fatima ([email protected]).
  CLEOPATRA project (a Marie Skłodowska-Curie Innovative Training Network)
  Prof E Simperl
Application Deadline: 2 April 2020

Funding Type

PhD Type

Applications are invited for a Marie Curie Early Stage Researcher position within the Department of Informatics, King’s College London, working with Professor Elena Simperl, staring as soon as possible.
  PhD Scholarship in Cognitive Science and Artificial Intelligence
  Prof P Cheng
Application Deadline: 24 April 2020

Funding Type

PhD Type

Applications are invited for a funded full-time three year PhD in Artificial Intelligence or Cognitive Science (stipend and fees).
  Ontology-based system for human movement experts
  Research Group: Computing, Informatics and Applications Research Group
  Dr C Luca, Dr F Cavallerio, Ms K McDonald
Applications accepted all year round

Funding Type

PhD Type

Research Group. Computing, Informatics and Applications Research Group and. Cambridge Centre for Sport and Exercise Sciences. (https://www.anglia.ac.uk/science-and-engineering/research/institutes-and-groups/cambridge-centre-for-sport-and-exercise-sciences).
  An interactive and intelligent User eXperience interface
  Dr H Yu, Prof J J Zhang
Application Deadline: 3 May 2020

Funding Type

PhD Type

The goal is two-fold, one is to give customers guidance for shopping, and another is to collect User eXperience (UX) data for product evaluation, design and development.
  Artificial Intelligence and Machine Learning for Biomedical Data
  Prof P Andras
Applications accepted all year round

Funding Type

PhD Type

Artificial Intelligence (AI) and Machine Learning (ML) are the leading edge approaches to data driven problems across all areas of life, technology and sciences.
  Computer Vision and Machine Learning for ReIdentification of Civil Structural Components and their Damage Analysis.
  Dr B Mandal
Applications accepted all year round

Funding Type

PhD Type

In this project the PhD research student needs to understand the strengths and weaknesses of the deep convolutional neural network for analysis of civil infrastructures, such as concrete bridges, highways, buildings, tunnels and stadiums, using videos/images captured by a network of multiple cameras.
  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.
  Developing a dynamic population model of disease and accompanying open source software tool
  Prof Christos Vasilakis, Dr L Piwek
Application Deadline: 20 April 2020

Funding Type

PhD Type

The University of Bath is inviting applications for the following PhD project based in the School of Management under the supervision of Professor Christos Vasilakis (https://researchportal.bath.ac.uk/en/persons/christos-vasilakis), Dr Lukasz Piwek (https://researchportal.bath.ac.uk/en/persons/lukasz-piwek) and Dr Richard Wood (https://www.linkedin.com/in/richard-wood-aa647188/).
  Computer Architectures for Probabilistic Robotics/Autonomous Systems Applications
  Dr P Stanley-Marbell
Applications accepted all year round

Funding Type

PhD Type

The Physical Computation Laboratory is seeking a PhD student to work on a project developing new **Computer Architectures for Probabilistic Robotics/Autonomous Systems Applications**.
  Hardware Implementations of Differential Privacy for Low-Power Energy-Scavenged Sensors
  Dr P Stanley-Marbell
Applications accepted all year round

Funding Type

PhD Type

The Physical Computation Laboratory is seeking a PhD student to work on a project developing new **Hardware Implementations of Differential Privacy for Low-Power Energy-Scavenged Sensors**.
  New Computer Architectures for Probabilistic Computer Vision
  Dr P Stanley-Marbell
Applications accepted all year round

Funding Type

PhD Type

The Physical Computation Laboratory is seeking a PhD student to work on a project developing new **Computer Architectures for Probabilistic Computer Vision Applications**.
  Sensor Scheduling Scheduling Algorithms for Low-Power Energy-Scavenged Sensors
  Dr P Stanley-Marbell
Applications accepted all year round

Funding Type

PhD Type

The Physical Computation Laboratory is seeking a PhD student to work on a project developing new **Sensor Scheduling Scheduling Algorithms for Low-Power Energy-Scavenged Sensors**.
  Data Science of Social Innovation
  Dr Y Eom
Application Deadline: 31 March 2020

Funding Type

PhD Type

The Centre for Doctoral Training in Data Science for Studying Science, Innovation and Entrepreneurship is looking for applicants for a PhD studentship in Data Science of Social Innovation, supervised by Dr Yashar Moshfeghi (Dept.
  Automatic Activity Analysis, Detection and Recognition
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Activity detection, analysis and recognition are related to several important areas in machine perception research and applications.
  Automatic Music Generation via Deep Learning
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Music appears as an art form and cultural activity whose medium is sound organized in time, which is an ultimate language for human beings.
  Biologically-Plausible Continual Learning
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Continual learning (aka lifelong learning) refers to a problem on how a learning system learns multiple tasks in succession over the lifespan where later tasks do not degrade the performance of the system learned for the earlier tasks and, ideally, the system can leverage the knowledge learned in previous tasks to facilitate learning the new tasks better.
  Contextualised Multimedia Information Retrieval via Representation Learning
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Multimedia Information Retrieval (MIR) is an important research area in AI that aims at extracting semantic information from multimedia data sources including perceivable media such as audio, image and video, indirectly perceivable sources such as text, bio-signals as well as not perceivable sources such as bio-information, stock prices, etc.
  Deep Learning for Temporal Information Processing
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Temporal information process covers a broad class of learning problems where knowledge can be acquired from data of a sequential order, e.g.
  Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Traditionally there are two main paradigms in machine learning, supervised vs. unsupervised learning.
  Information Component Analysis via Deep Learning
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

As their prominent characteristics, perceptual data often convey the mixing information, which often results in the inadequate performance for a specific perceptual information processing task due to the interference of irrelevant information components.
  Machine Learning and Cognitive Modelling Applied to Video Games
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Video games have been viewed as an ideal test bed for the study of AI. However, most of the academic work in this area focused on traditional board and card games where limited AI techniques have been tested.
  Multi-task Learning and Applications
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

In traditional machine learning, a learning system can be trained to deal with a specific single task, while human is able to complete multiple tasks with the same learning strategy.
  Zero-Shot Learning and Applications
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Zero-shot learning refers to a novel paradigm on learning how to recognise new concepts by just having a description of them. For example, zero-shot learning works on a setting of solving a classification problem when no labelled training examples are available for all classes, which are divided into two class subsets.
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