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learning PhD Projects, Programs & Scholarships

We have 471 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.
  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.
  Exploring “Learning Spaces” in Teaching English to Speakers of Other Languages (TESOL)
  Dr R Shanks, Dr V Greenier
Applications accepted all year round

Funding Type

PhD Type

This study will explore the ways in which the physical learning environment (i.e.
  Social Learning in Artificial Evolutionary Systems
  Dr J Borg
Applications accepted all year round

Funding Type

PhD Type

Artificial evolutionary systems, be they simulated or grounded in physical robots, provide a novel and cutting-edge way to investigate the emergence and evolution of adaptive and intelligent behaviours.
  Developing a new learning algorithm for biologically inspired spiking neural networks
  Dr A Taherkhani, Prof TM McGinnity, Dr G Cosma
Applications accepted all year round

Funding Type

PhD Type

The brain’s processing ability to solve complex problems has inspired many researchers to investigate how the brain processes information, reasons and its learning mechanisms.
  PhD Studentship in Deep Learning for Modelling Complex Video Activities
  Prof F Cuzzolin
Application Deadline: 4 October 2019

Funding Type

PhD Type

Eligibility. UK ,EU & International candidates. Bursary. £16,000 per year (no annual inflation increase). Fees. Tuition fees will be paid by the University.
  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.
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