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PhD Studentship: Adaptive Sensing for Energy-Efficient Reinforcement Learning

Coventry University - Centre for Computational Science and Mathematical Modelling

Qualification Type: PhD
Location: Coventry
Funding for: UK Students, EU Students, International Students
Funding amount: Tuition fees and stipend
Hours: Full Time
Placed On: 20th November 2023
Closes: 20th February 2024
Reference: CSMR004

Reinforcement Learning (RL) is a one of the three major machine learning approaches, together with supervised and unsupervised learning, and which has raised in popularity in recent years. As Reinforcement Learning moves closer to real-world applications, in particular within sensor-based applications, the energy consumed by sensors becomes a significant concern. IoT devices and robots often operate on limited power sources, such as batteries. The overall objective of this project is to develop RL agents that optimize the use of sensor data to save energy in IoT devices and robotic platforms. This will involve the development of an RL framework where the agent not only learns to take actions in its environment but also decides when to activate or deactivate certain sensors. The RL agent must learn to trade-off between the information it receives from sensors and the energy consumed to acquire that information. The expected real-world impact of this project is to enhance the operational lifespan of battery-powered devices and robots in many of the real-world sensing-based applications, by making them more energy efficient.

The successful applicant will start with developing a solution that can work in a simulated environment and then gradually include additional real-world aspects. It is expected that, throughout the PhD programme, the applicant will be interacting and collaborating with the industry contacts to ensure that the approach meets their needs. The final goal is to provide the industry with a solution that can be brought to market and used within robotics and other sensor-based applications.

Entry criteria for applicants to PhD

  • A bachelor’s (honours) degree in a relevant discipline/subject area with a minimum classification of 2:1 and a minimum mark of 60% in the project element (or equivalent), or an equivalent award from an overseas institution.

PLUS

  • the potential to engage in innovative research and to complete the PhD within 3.5 years
  • An adequate proficiency in English must be demonstrated by applicants whose first language is not English. The general requirement is a minimum overall IELTS Academic score of 7.0 with a minimum of 6.5 in each of the four sections, or the TOEFL iBT test with a minimum overall score of 95 with a minimum of 21 in each of the four sections.

For further details please visit:  https://www.coventry.ac.uk/research/research-opportunities/research-students/making-an-application/research-entry-criteria/

https://www.coventry.ac.uk/research/research-opportunities/research-students/making-an-application/

The applicant is not required to submit a research proposal as part of their application. Within the supporting statement, candidates should articulate why they believe they are suited for this position. Specifically, we anticipate that the applicant will demonstrate some experience/and or knowledge pertinent to machine learning and will have good programming skills.

To find out more about the project please contact Prof. James Brusey at aa3172@coventry.ac.uk

All applications require a covering letter and a 2000-word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project.  

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