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Postgraduate research project

Machine learning for multi-robot perception

类型的程度
哲学博士
学院研究生院
Faculty of 英格ineering and Physical Sciences
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We are looking for a talented PhD student (fully funded) to work on the intersection of machine learning and swarm robotics. The goal of this PhD project is to propose a collective decision-making strategy and a learning model for robots that would lead to precise mapping of unknown environments.

Machine learning models such as generative adversarial networks can generate data (e.g. images) that have not been measured or obsevered before. One of the use cases for the generated data is to build novel perceptions of an unforeseen environment. This PhD project focuses on using machine learning on a large robot swarm that have partial observations of an environment and the idea is to coordinate these models in a way that a complete picture of the environment can be constructed.

In this project, you will gain a deep understanding of:

  • novel algorithms in machine learning,
  • 图像处理
  • 多机器人系统.

Successful candidates would have a strong background in computer science and preference would be given to those with good understanding of machine learning, formal methods and good programming skills. 你将加入 School of Electronics and Computer Science which is ranked 1st in the UK for Electrical and Electronic 英格ineering (Guardian University Guide 2022) within the KOK体育官方网站 which is ranked in the top 1% of universities worldwide.

You will be supervised by world leading researchers in their field and join an exceptional and vibrant team of postdoctoral researchers and other PhD 学生. You will benefit from the training and networking activities in the UKRI’s Trustworthy Autonomous Systems’ Hub and the EPSRC Smart Solutions Towards Cellular-Connected Unmanned Aerial Vehicles System (AUTONOMY) project. We will support the development of your future career (networking with more than 100 industry partners and universities across the UK) and give you opportunities to expand your experience and knowledge beyond the topic of the PhD project.

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