University of East Anglia Featured PhD Programmes
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learning PhD Projects, Programs & Scholarships

We have 1,050 learning PhD Projects, Programs & Scholarships

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  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.
  Learning to Learn: Multi-Task learning, transfer learning and meta-learning
  Dr V Ojha
Applications accepted all year round

Funding Type

PhD Type

Multi-task learning, transfer learning, and meta-learning are three dimensions (sub-fields) of learning techniques, strategies and frameworks currently being investigated in machine learning communities.
  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.
  Self-Supervised Learning and Variational Inference for adaptation in Deep Learning
  Dr G Leontidis
Application Deadline: 1 June 2020

Funding Type

PhD Type

We are looking for a highly motivated prospective PhD student to undergo a 3-year fully funded PhD project on Machine/Deep Learning foundations/theory and applications within the Department of Computing Science at the University of Aberdeen (UoA).
  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.
  SFI Centre for Research Training in Machine Learning

Funding Type

PhD Type

The SFI Centre for Research Training in Machine Learning addresses the urgent industry demand for Machine Learning talent. The centre brings together leaders in their field to supervise and train students.
  Multi-modal Data fusion using Deep Learning
  Dr G Cosma
Applications accepted all year round

Funding Type

PhD Type

Deep learning is a subset of machine learning in artificial intelligence (AI) that is capable of learning from data.
  SFI Centre for Research Training in Machine Learning

Funding Type

PhD Type

The SFI Centre for Research Training in Machine Learning addresses the urgent industry demand for Machine Learning talent. The centre brings together leaders in their field to supervise and train students.
  SFI Centre for Research Training in Machine Learning

Funding Type

PhD Type

The SFI Centre for Research Training in Machine Learning addresses the urgent industry demand for Machine Learning talent. The centre brings together leaders in their field to supervise and train students.
  Hierarchical reinforcement learning for PCB design
  Dr O Şimşek
Application Deadline: 21 June 2020

Funding Type

PhD Type

The University of Bath is inviting applications for a fully-funded PhD position open to UK and EU applicants. OVERVIEW OF THE RESEARCH PROJECT.
  Source-code similarity detection using deep learning
  Dr G Cosma
Application Deadline: 1 September 2020

Funding Type

PhD Type

Deep learning is a subset of machine learning in artificial intelligence (AI) that is capable of learning from data.
  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.
  Machine learning for Autonomous and Interconnected Vehicles
  Research Group: Applied Computing
  Dr ARA Abdullatif, Dr S Kabir, Dr I Ghafir
Applications accepted all year round

Funding Type

PhD Type

Cyber-Physical Mechatronic Systems such as autonomous vehicles, and intelligent transportation rely heavily on machine learning techniques for ever-increasing levels of autonomy.
  Towards a functional model for associate learning and memory formation
  Dr J Liu, Prof R Quian Quiroga
Application Deadline: 7 June 2020

Funding Type

PhD Type

The aim of this project is to study the most up-to-date experimental data regarding single-neuron and network learning and coding in humans, with the expectation that a functional model could be established thereon.
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