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PhD studentships, funding and fees

Finding funding is an important element of the application process and we recommend that you begin to explore your funding options as early as possible.

There are a range of different sources of funding available for PhD students at Queen Mary – in fact, we offer 220 fully or partially funded studentships. A PhD studentship is a funded postgraduate studentship opportunity either attached to a specific research project or open to postgraduate research applicants in a specific field or academic school.

Applications are open for the following PhD Studentships in the School of Electronic Engineering and Computer Science:

PhD titleResearch groupSupervisorClosing date

QMUL/EPSRC PhD Studentships

Antennas & Electromagnetics Prof. Yang Hao 10/08/2018

ICASE PhD STUDENTSHIP in Network Design with BT

Operational Research  Dr. John Drake, Dr. Jun Chen, Prof. Edmund Burke  31/08/2018

PhD Studentship in passive and active antennas and quasi-optical devices for mm-and THz applications

Antennas & Electromagnetics Dr. Rostyslav Dubrovka 01/09/2018

 PhD Studentships in Machine Learning for Autonomous Systems


Centre for Intelligent Sensing  
Dr. Riccardo Mazzon   07/09/2018

PhD Studentship in When Machine Learning Meets Big Data in Wireless Communications

 
Communication Systems Research Dr. Yuanwei Liu   18/09/2018

PhD Studentship in Machine Learning for Automated Software Engineering


Operational Research

Dr. John Drake, Dr. John Woodward, Prof. Edmund Burke


Early applications advised

 

Other studentship opportunities

You can also search for studentships on the Queen Mary where you can filter your search via study level, school, country. At the School of Electronic Engineering and Computer Science, we receive a number of applications from the following schemes each year:

 


 

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QMUL/EPSRC PhD Studentships


Application closing date: 10/08/2018
Start date: 1 September 2018 (or as soon as possible thereafter)
Research group: Antennas and Electromagnetics

Duration: 3.5 years
Funding available

Applications are invited for up to eight PhD Studentships, to undertake research in the area of smart/tunable materials, nanotechnologies, antennas and electromagnetics in collaboration with UK industries including Qinetiq, Thales UK and Huawei Technologies from September 2018, or as soon as possible thereafter. The studentships are based at the School of Electronic Engineering and Computer Science at Queen Mary, University of London and will be supervised by Prof. Yang Hao (FIEEE) of the Antennas and Electromagnetics Group and other colleagues across the Faculty of Science and Engineering. The studentships will involve the development of machine-learning algorithms in material modelling and control system designs. It is expected that the students will work in close collaboration with other postdoctoral researchers funded by the EPSRC ANIMATE project on Software Defined Materials under EP/R035393/1, both in QMUL and partner industry.


Candidates should have a first or upper second class honours degree or equivalent (and preferably a Masters Degree) in any relevant area including Electronic and Computer Engineering, Mathematics, Physics, Material Science or a related field, and the ability to demonstrate strong mathematical and analytical skills. Good programming skills and background in electromagnetics are also desirable.


One of these studentships, funded by Thales UK and an EPSRC Doctoral Training Account, is for fees plus a tax-free stipend starting at £15,726 per annum. It is a CASE award and attracts an additional stipend of £5,200 per annum from the industrial partner. Further details of the EPSRC scheme including terms and conditions can be found here: https://epsrc.ukri.org/skills/students/. Due to funding restrictions applicants must satisfy UK residence requirements as defined here: www.epsrc.ac.uk/skills/students/help/Pages/eligibility.aspx


Other studentships will be available for all candidates including European and overseas students. We are valuing diversity and committed to equality.
Informal enquiries can be made by email to Prof. Yang Hao. To apply please follow the on-line process by selecting “Electronic Engineering” in the “A-Z list of research opportunities” and following 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 of Research Interest should answer two questions: (i) Why are you interested in the proposed area?  (ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper.  In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper.  More details can be found at: http://www.eecs.qmul.ac.uk/phd/how-to-apply.php

     
Interviews are expected to take place between August 23 and 31, 2018.

 

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ICASE PhD STUDENTSHIP in Network Design with BT


Application closing date: 31/08/2018
Start date: October 2018
Research group: Operational Research

Duration: 3 years
Funding available

The Operational Research Group within the School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL), invites applications for a fully-funded PhD Studentship to undertake research in the area of Network Design Optimisation in collaboration with BT University Research. The studentship will start from 1st October 2018, or as soon as possible thereafter. The studentship will be based at the School of Electronic Engineering and Computer Science at QMUL and will be supervised by Prof Edmund Burke, Dr Jun Chen and Dr John Drake.

The studentship will investigate applications for network design, e.g. a town’s fibre network. The goal of the project is to explore software solutions to find optimal solutions to a graph problem described in a human readable declarative constraint language. It has two parts.

  • Design a declarative language for representing constraints on a graph, and the costs of the graph.
  • Implement a heuristic search engine which combines heuristic search techniques with constraint satisfaction methods to limit the search space. It is expected that the students will work in close collaboration with other researchers, both in QMUL and BT University Research.

Candidates should have a first class honours degree or equivalent (and preferably a Masters Degree) in Computer Science or a related field, and the ability to demonstrate mathematical and analytical skills. Strong programming skills and background in heuristics, metaheuristics, constraint handling and graph theory are also desirable. Successful applicants should have a clear commitment to research and should enjoy working at the intersection of theory and practice.

This studentship, funded by an EPSRC ICase, is for tuition fees plus a tax-free stipend starting at approximately £16.5K per annum. It attracts an additional stipend from the industrial partner. Further details of the EPSRC scheme including terms and conditions can be found here: https://www.epsrc.ac.uk/skills/students/

Applicants must satisfy UK residence requirements as defined here: https://www.epsrc.ac.uk/skills/students/help/eligibility/

Informal enquiries are strongly advised before application, and can be made by email to Dr Jun Chen and Dr John Drake .

To apply please follow the on-line process (see www.qmul.ac.uk/postgraduate/apply/) by selecting “Computer Science” in the “A-Z list of research opportunities” and following the instructions on the right hand side of the web page. Applications received directly by email will not be accepted. 

Please note that instead of the 'Research Proposal' we request a 'Statement of Research Interests'. Your Statement of Research Interest should answer two questions: (i) Why are you interested in the proposed area?  (ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper.  In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper.  More details can be found at: http://www.eecs.qmul.ac.uk/phd/how-to-apply/

The closing date for applications is 31 August 2018.      

Interviews are expected to take place after 01 September 2018.

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PhD Studentship in passive and active antennas and quasi-optical devices for mm-and THz applications


Application closing date: 01/09/2018
Start date: no later than January 2019
Research group: Antennas and Electromagnetics

Duration: 3 years
Funding available

Modern communication systems and special microwave applications like security tend to move towards higher frequency bands, namely, mm-, sub-mm and THz regions. Novel solutions are required to implement emerging technologies.

The recent advances in the Antennas and Electromagnetics Group have shown that it is possible to realise elements of mm- and sub-mm wave ranges using so-called quasi-optical networks and devices. However, deeper insight into such systems, including combined active/passive devices, e.g., antenna with amplifier, is under particular interest and is very timely.

This fully funded research studentship aims to discover new theoretical and practical realisations and design of aforementioned devices and antennas.

All applicants should hold a masters level degree at first /distinction level in electronic engineering or radiophysics. Candidates are asked to possess fundamental knowledge and skills in one or more of the following areas:

  • Electromagnetic and antenna theory
  • Classic and long-wave (quasi) optics
  • Basic circuit theory with emphasis on active and non-linear operational modes
  • Measurement experience using a VNA or THz-TDS
  • Basic knowledge of spectroscopy
  • Basic knowledge of Physic
  • MATHEMATICS – Applied, Mathematical Physics

Strong motivation to aim for excellence is essential, as are good communication skills.

Details about the Antennas and Electromagnetics Group can be found at: antennas.eecs.qmul.ac.uk

All nationalities are eligible to apply for this studentship. We offer 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. The first supervisor is Dr. Rostyslav Dubrovka. In addition to the studentship, we also welcome applications from self-funded students with relevant background or experience.

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. More details can be found at: http://www.eecs.qmul.ac.uk/phd/apply.php

Please, note that the main subject of offered PhD study is “Passive and active antennas and quasi-optical devices for mm- and THz applications”. Hence, your Statement is supposed to be closely connected to the detailed list of suggested topics which can be found at Project Ideas or at http://eecs.qmul.ac.uk/profiles/dubrovkarostyslav.html.

Applicants seeking further information or feedback on their suitability are encouraged to contact Dr. Rostyslav Dubrovka with subject “THz Antennas & QO Devices PhD”. However, please, do not send documents as they will be reviewed only after the deadline.

The closing date for applications is 1 September 2018.      

Interviews are expected to take place in the end of September 2018.

Starting date: Not later than January 2019 (dates can be flexible).

 

PhD Studentship in Machine Learning for Automated Software Engineering


Application closing date: 07/09/2018
Start date: in 2018
Research group: The Centre for Intelligent Sensing

Duration: 3 years
Funding available

The Centre for Intelligent Sensing at Queen Mary University of London invites applications for a 2 PhD Studentships to undertake research in the area of Machine Learning for Autonomous Systems. The PhD projects can focus on theory and application of visual and/or audio and/or radio sensing: data processing and machine learning, computer vision, intelligent networks, communication and cognitive radio.

All nationalities are eligible to apply for this studentship, to be ideally started in 2018. The studentship is for three years, and covers student fees as well as a tax-free stipend.

This PhD project is part of an interdisciplinary collaboration on Interactive and Cognitive Environments between the Centre for Intelligent Sensing at Queen Mary University of London (QMUL) and the Department of Electrical, Electronic, Telecommunication, and Naval Engineering at University of Genoa (UNIGE), Italy. The studentships will be based in the School of Electronic Engineering and Computer Science (EECS) at QMUL in London, with a period of time, normally of 12 months, spent at UNIGE. The list of potential QMUL supervisors can be found here: cis.eecs.qmul.ac.uk/people

Candidates should have a first-class honours degree or equivalent, or a good MSc Degree, in Computer Science, Physics, Mathematics or Electronic Engineering. Candidates must be confident in applied mathematics, and should have good programming experience, in particular C/C++, Python and MATLAB environment. Previous knowledge of Signal Processing or Machine Learning is required.

To apply please follow the on-line process at
www.qmul.ac.uk/postgraduate/applyresearchdegrees by selecting Electronic Engineering or Computer Science in the A-Z list of research opportunities and following 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 of Research Interest should answer two questions: Why are you interested in the proposed area? What is your experience in the proposed area? In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper.

For more information and to apply, please visit: www.eecs.qmul.ac.uk/phd/apply

Informal enquiries can be made by email to Dr. Riccardo Mazzon.

The closing date for the applications is 7 September 2018.

Interviews are expected to take place during the week commencing 10 September 2018.

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 PhD Studentship in When Machine Learning Meets Big Data in Wireless Communications


Application closing date: 18/09/2018
Start date: November 2018-April 2019
Research group: Communication Systems Research

Duration: 3 years
Funding available

Recent several decades have witnessed the exponential growth in commercial data services, which lead to step in the so-called big data era. The pervasive increasing data traffic present both the imminent challenges and new opportunities to all aspects of wireless system design, such as efficient wireless caching, drone base station deployment and adaptive nonorthogonal multiple access design. Machine learning, as one of the most promising artificial intelligence tools, has been invoked in many areas both in the academia and industry. Nevertheless, the application of machine learning in wireless communication scenarios is still in its infancy, which motivates to develop this phD project. 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.

Qualifications:
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).

All nationalities are eligible to apply for this studentship. We offer 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. The first supervisor is Dr. Yuanwei Liu . In addition to the studentship, we also welcome applications from students supported by other funding with relevant background or experience.

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. More details can be found at: www.eecs.qmul.ac.uk/phd/apply

Applicants seeking further information or feedback on their suitability are encouraged to contact Dr. Yuanwei Liu with subject “Machine Learning & Wireless Communications PhD”. However, please, do not send documents as they will be reviewed only after the deadline.

The closing date for the applications is 18th September 2018.
Interviews are expected to take place in the end of September/beginning of October 2018.
Starting date: November 2018- April 2019 (dates can be flexible).

 

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PhD Studentship in Machine Learning for Automated Software Engineering


Application closing date: early application advised
Start date: September 2018 
Research group: Operational Research

Duration: 3 years
Funding available

The Operational Research Group within the School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL), invites applications for a fully-funded PhD studentship to work on a project funded by the Engineering and Physical Sciences Research Council.

The DAASE Project (http://daase.cs.ucl.ac.uk/about/) is an EPRSC funded project involving QMUL, University College London, The University of Birmingham, The University of Stirling, and The University of Sheffield. Our industrial partners include Berner and Mattner, BT Laboratories, Ericsson, GCHQ, Honda Research Institute Europe, IBM, Microsoft Research and Motorola UK. It involves around 50 academics working over 6 years with £6.8M funding.

The successful candidate will pursue a course of research investigating the application of computational search methods, to software engineering challenges with a focus on real-world applications. These techniques could include machine learning approaches, big data techniques, and more broadly any metaheuristic, or operational research technique.

DAASE is a highly collaborative project involving 5 UK universities. The successful candidate will have opportunities to visit and work with industrial and other partners and to be fully engaged with the international community through conferences, workshops and other networking activities. This will enhance their training and development and open new opportunities for collaboration and intellectual development. Students will also have the opportunity to engage with researchers within the OR group working on other projects in a variety of application domains.

All nationalities are eligible to apply for this studentship, which will start on 1st September 2018, however an earlier start date is possible for excellent candidates. The studentship is for three years, and covers international student fees as well as a tax-free stipend of around £16,500 per annum.

Candidates are expected to have a first class honors degree or Masters in Computer Science, Mathematics, Operational Research or related discipline, from a UK University or an equivalent standard from an overseas university. The successful candidate must have a strong programming background, as well as good analytical and communication skills. The student is expected to work as part of a team and independently, and to prepare clear reports and research papers. An understanding of mathematical optimisation techniques, heuristic and hyper-heuristic search is highly desirable although not mandatory.

Informal enquiries can be made by email to Dr. John Drake and Dr. John Woodward who will supervise the project alongside Prof. Edmund Burke. Informal enquiries are strongly encouraged before a candidate submits an application.

For more information and to apply, please visit: http://www.eecs.qmul.ac.uk/phd/how-to-apply/

The post will be held open until it is filled, so early application is highly advisable.

 

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