All nationalities are eligible to apply for this studentship. The offer is a 3-year fully funded PhD studentship supported by Queen Mary University of London including student fees and a tax-free stipend starting at £17,609 per annum. In addition to the studentship, we also welcome applications from self-funded students with relevant backgrounds.
Scholarship Sponsor(s): Queen Mary University of London, UK
Host Institution(s): Queen Mary University of London, UK
Scholarship Worth: £17,609 per annum
Number of Awards: Several
Study Level: PhD
Nationality: International Students
DETAILS | Queen Mary University of London PhD Studentship
This studentship will explore the intersection of Edge/Serverless and ML/AI for modern IoT applications. The scope of the project is quite broad. Applicants are encouraged to suggest their own interest and refine the research direction accordingly.
The PhD will be supervised by Dr Sukhpal Singh Gill and will be based in the Networks Research Group, an interdisciplinary group with strong publication record and high international impact, which is part of the School of Electronic Engineering and Computer Science, Queen Mary University of London, UK.
To be eligible for Queen Mary University of London PhD Studentship, applicants are expected to meet the following conditions:
- All applicants should have a first-class honour degree or equivalent, or a MSc degree, in Computer Science or Electronic Engineering (or a related discipline).
- Applicants should have a good knowledge of English and ability to express themselves clearly in both written and spoken form.
- The successful candidate must be strongly motivated to undertake doctoral studies, as well as must have demonstrated the ability to work independently and perform critical analysis. A record of publishing research in international conferences and/or journals is highly desirable, as well as a strong track record of working in international teams.
The essential selection criteria will include:
- Experience in Cloud, Edge, Serverless Computing.
- Good coding skills in Python, Matlab and/or Java.
- Good knowledge of data science methods.
- Understanding of Machine Learning and IoT.
- Ability to work independently or as part of a team.
The desirable selection criteria will include:
- Experience and knowledge of machine learning techniques.
- Experience in action and activity recognition.
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How-to-Apply: To apply, please follow the online instructions specified by the college website for research degrees: http://www.eecs.qmul.ac.uk/phd/how-to-apply/. Steps 2 onwards are applicable in this case. Please note that we request a ‘Statement of Research Interests’. Your statement (no more than 500 words) should answer two questions:
(i) Why are you interested in the topic described above?
(ii) What relevant experience do you have?
In addition to this, we would also like you to submit a sample of your written work. This might be a chapter of your final year or masters dissertation, or a published conference or journal paper.
In order to submit your online application you will need to visit the following webpage: https://www.qmul.ac.uk/postgraduate/research/subjects/computer-science.html. Please scroll down the page and click on “PhD Full-time Computer Science – Semester 2 (January Start)”. The successful PhD candidate will be a member of the Networks Research group. You should mention this in your application.
Application Deadline: Not Stated