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We have 56 transfer learning PhD Projects, Programmes & Scholarships

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transfer learning PhD Projects, Programmes & Scholarships

We have 56 transfer learning PhD Projects, Programmes & Scholarships

Self-Supervised Learning for Complex Visual Understanding

94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021. The aim of this PhD project is to advance the state-of-the-art in computer vision through the development and application of self-supervised learning (SSL) techniques. Read more
Last chance to apply

Enhancing Healthcare Applications Through Cost-effective AI Solutions

This is a four year collaborative studentship which requires the candidate to spend two full years based at Coventry University (UK) and two years based at A*STAR Research Institute (Singapore). Read more

Doctorates in Education and Lifelong Learning

Doctorates in Education and Lifelong Learning. UEA's postgraduate degree programmes (PhD, EdD, EdPsyD) in the School of Education & Lifelong Learning are designed to explore and contribute to local, national and international education. Read more

Education PhDs at a leading university

Doctorates in Education and Lifelong Learning . UEA's postgraduate degree programmes (PhD, EdD, EdPsyD) in the School of Education & Lifelong Learning are designed to explore and contribute to local, national and international education. Read more

Data-Centric Solutions for Earth Observation Challenges: Developing Cutting-Edge Techniques for Remote Sensing Analysis [SELF-FUNDED STUDENTS ONLY]

In today's data-driven landscape, the importance of data-centric machine learning methodologies cannot be overstated where they prioritize the quality, diversity, and accessibility of data, recognizing that the performance and reliability of machine learning models heavily depend on the data they are trained on. Read more

Data-Centric Solutions for Earth Observation Challenges: Developing Cutting-Edge Techniques for Remote Sensing Analysis

In today's data-driven landscape, the importance of data-centric machine learning methodologies cannot be overstated where they prioritize the quality, diversity, and accessibility of data, recognizing that the performance and reliability of machine learning models heavily depend on the data they are trained on. Read more

Clinical Prediction Modelling under Federated Learning

Clinical prediction models (CPMs) take a set of characteristics about a patient to estimate their risk of an event of interest. Developing CPMs using data that captures observations across multiple clusters (e.g., countries) can increase the robustness and generalisability of CPMs. Read more

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