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PhD Studentship: Reinforcement Learning Techniques for Fleets of Autonomous Vehicles

University of Bristol - Electrical & Electronic Engineering

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students
Funding amount: £18,000 + per annum
Hours: Full Time
Placed On: 7th January 2019
Closes: 31st August 2019

The project:

This project will explore a new paradigm of learning from interactions with the environment to achieve network control functions, which in turn can orchestrate networks of autonomous vehicles.   

Traditionally, optimal control was being provided using heuristics guided by domain expertise. With ML showing unprecedented benefits in such as diverse domains as image classification, natural language processing, automated driving and anomaly detection, it is natural to attempt to reap the benefits for a range of problems in telecommunication industry. Specifically, this project will utilise Reinforcement Learning (a sub branch of AI) which is particularly suitable for a range tasks in network control such as Self Organising-Networks, Resource Allocation any more. RL is a revolutionary paradigm shift, already successfully applied to computer games (e.g. DeepMind’s AlphaGo & AlphaZero). Computer games are a natural training ground for continuous control problems.  Computer games as well as many topics in network control can be modelled using Markov Decision Processes (MDP), and hence fundamental solutions developed for playing games are in principle transferable on any other problem modelled by MDP. In this project we focus on Deep Reinforcement Learning (DRL). DRL leverages universal function approximation capabilities of deep neural networks to vastly improve scalability of traditional RL techniques. DRL for orchestration of automated vehicles’ fleets is very much in its infancy. Therefore, there are significant opportunities to conduct ground breaking research with tremendous societal impact.  

The successful PhD student will join a large team composed of UK Leading Universities and BT, working on recently funded Next Generation Digital Converged Infrastructure (NGCDI) Project.  

How to apply:

Please make an online application for this project at Please select < Electrical & Electronic Engineering> on the Programme Choice page and enter details of the studentship when prompted in the Funding and Research Details sections of the form.

(Overseas candidates please contact before filing your application)

Candidate requirements: 

An enthusiastic student with a minimum 2:1 honours degree or equivalent in Electrical & Electronic Engineering, Computer Science, Physics, Maths.

Basic skills / knowledge required in Solid Mathematics (Statistics, Multivariate Calculus, Optimisation, Matrix Algebra) and Programming (Python, Tensorflow)


The studentship is co-funded for 4 years by EPSRC and industrial partner British Telecom Ltd.  The eligibility criteria are listed on EPSRC website.  The stipend is £18K, £18.5K, £18.5K, £19K (in years 1-4). Substantial allowance for conference travel and consumables is also provided.   


Informal enquiries, Dr Robert Piechocki,

General enquiries, please email

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