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PhD Studentship: Learning Transmission Strategies for Internet of Things

A fully-funded PhD studentship is available to home UK students .

Duration of study: Full Time- three years fixed term

Starting date: December 2016

Application deadline: 14th November 2016 (or until filled)

Supervisor: Dr Laura Toni

A fully-funded PhD studentship is available to home UK students within the project of learning transmission strategies for IoTs. The studentship is available from 1st December 2016, for a period of three years. The student will work under the supervision of Dr. Laura Toni within the Communication and Information System at UCL.

The Internet of Things (IoT), smart connected devices able to gather and process data locally and in real-time, will radically disrupt many different aspects of our daily routine, from commuting through self-driving cars to urban planning in smart cities, leading to a fully connected world. By 2020, 50 billions of devices will be connected to the Internet, smartly generating, sharing and processing data.

This is expected to exceed the design specifications and limits of existing networking systems. Future communication networks therefore will need to be opportunistically designed with adaptive and distributed protocols. This will be possible jointly learning the environment (e.g., network status) while adapting to it. Reinforcement learning (RL) theory achieves this goal but mainly in small-scale networks, while envisioned IoT networks are high-dimensional. An open challenge is how to advance RL theory to make learning and adaptive strategies data-efficient in large-scale networks and how to turn these theoretical findings into practical communication paradigms.


Applicants must hold, or be near completion of a first or upper-second class degree in Electrical Engineering or a related subject. An understanding of machine learning and optimization algorithms is required. The ideal candidate would also have a strong interest in computer programming, communications systems. We are seeking candidate with the potential to engage in innovative research and to complete the PhD within a three-year period of study. Fluent English is also required.


Also, the candidate is expected to:

  • • Have excellent analytical and engineering skills
  • • Have excellent reporting and communication skills
  • • Be self-motivated, independent and team player
  • • Have genuine enthusiasm for the subject and technology
  • • Have the willingness to author and publish research findings in international journals
  • Be eligible for home UK studentship:


The studentship is available for three years and covers tuition fees at the UK rate, plus a stipend at £16,296 pa (tax free).

Informal enquiries should be addressed to Dr Laura Toni ( by 14th November 2016 (or until filled).

Formal applications should be submitted with a CV, a brief statement of your research interests, and with names and email addresses of two referees.

You can also download a copy of this advert.