The School of Electronic Engineering and Computer Science at Queen Mary University of London is inviting applications for PhD Studentship in When Machine Learning Meets Big Data in Wireless Communications.
The aim of this PhD project is to use social media data to predict the requirements of mobile users for improving the performance of wireless networks.
User Review( votes)
The School of Electronic Engineering and Computer Science is one of the oldest departments of its kind in Britain. Did you know we helped set up the first internet node in the UK and were the first to provide the now popular Apple/Unix workstations for students.
- Applications Deadline: September 18, 2018
- Course Level: Studentship is available to study PhD programme.
- Study Subject: Studentship is awarded in When Machine Learning Meets Big Data in Wireless Communications.
- Scholarship Award: The studentship offers a 3-years fully funded PhD studentship, with a bursary ~£16.5K/year and a fee waiver (including non-EU students), supported by the School of Electronic Engineering and Computer Science of the Queen Mary University of London, UK.
- Nationality: All nationalities are eligible to apply for this studentship.
- Number of Scholarships: Numbers not known
- Scholarship can be taken in the UK
Eligibility for the Scholarship
Eligible Countries: All nationalities are eligible to apply for this studentship.
Entrance Requirements: Applicants must meet the following criteria:
All applicants should hold a masters level degree at first /distinction level 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 speech and writing. The successful candidate must be strongly motivated for doctoral studies, must have demonstrated the ability to work independently and to perform critical analysis.
Candidates are asked to possess fundamental knowledge and skills in two or more of the following areas:
• Excellent background in communication theory and signal processing algorithms. Good knowledge of emerging 5G and IoT techniques, such as NOMA, wireless caching and mobile computing, UAV, V2X, etc.
• Prior experience/education in both theory and practice of machine learning.
• Hands on experience using one of the following deep learning libraries: Tensorflow, PyTorch, Theano or similar.
• Good coding skills. (Python and C++ are considered a plus).
English Language Requirements: Applicants should have a good knowledge of English and ability to express themselves clearly in both speech and writing.
How to Apply: To apply, please follow the on-line instructions at the college web-site for research degree applicants. At the page, select ‘Electronic Engineering in the list “FIND”’ and follow the instructions on the right-hand side of the web page. Please note that instead of the ‘Research Proposal’ 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?
Please attach your CV, a transcript of records, and the title/s of your MSc dissertation/s.
In addition, we would also like you to send a sample of your written work, e.g., a chapter of your final year dissertation, or a published paper.