PhD Studentship in Machine Learning and IoT
|Applications Close: 14th February 2020
Start date: April 2020
Research group: Communication Systems Research (CSR) Group
Duration: 3 years
Applications are invited for a full PhD Scholarship starting April 2020 (or as soon as possible thereafter) to undertake research in the area of Machine learning and IoT in the context of Smart Cities.
Innovations in smart cities, mobility, and transport are starting to tap into the world of ML and IoT but the applicability and exportability of IoT/ML solutions remain limited due to the vast differences between the characteristics of cities and regions. An ML algorithm that is trained to detect violence on the streets of Oslo may fail to perform in cities such as Tokyo, or an autonomous pod trained to deliver groceries in Oxford may be disoriented when facing the traffic in Beijing. In contrast, people would be able to perform these tasks with satisfactory results anywhere in the world, even on their first visit, by using their common-sense.
This project looks at investigating the outcomes of the intersection of ML and IoT in the context of smart cities, transport, or mobility in general. The scope of the project is quite broad and diverse and students are encouraged to explore their own interest and refine the research direction accordingly.
The PhD will be supervised by Dr Mona Jaber and will be based in the QMUL Communication Systems Research (CSR) Group (http://csr.eecs.qmul.ac.uk//), an interdisciplinary group with strong publication record and high international impact, which is part of the School of Electronic Engineering and Computer Science (http://www.eecs.qmul.ac.uk), Queen Mary University of London, UK.
All applicants should have a first-class honour degree or equivalent, or an 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 would be highly desirable, as well as a strong track record of working in international teams.
The essential selection criteria include:
- Experience in Machine Learning.
- Good knowledge of data science methods.
- Understanding of IoT networks and data.
- Good coding skills in Python, Matlab and/or C++.
- Ability to work independently or as part of a team.
The desirable selection criteria include:
- Experience and knowledge of deep learning techniques (e.g., computer vision application).
- Experience in action and activity recognition.
All nationalities are eligible to apply for this studentship. We offer a 3-year fully-funded PhD studentship supported by Queen Mary University of London including student fees and a tax-free stipend starting at £17,009 per annum. In addition to the studentship, we also welcome applications from self-funded students with relevant backgrounds.
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 Communication Systems Research group. You should mention this in your application.
Applicants interested in the post, seeking further information or feedback on their suitability are encouraged to contact Dr Mona Jaber at m,firstname.lastname@example.org with subject “Machine Learning and IoT PhD Studentship”. All applications must be made via the website mentioned above.