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We have 26 Communications Engineering (environment) PhD Projects, Programmes & Scholarships

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Communications Engineering (environment) PhD Projects, Programmes & Scholarships

We have 26 Communications Engineering (environment) PhD Projects, Programmes & Scholarships

Causal Machine Learning in Aerospace PhD

This PhD project will investigate the recent field of study of Causal Machine Learning, which aims to modify and augment Machine Learning by using Causal Analysis techniques as a way to solve its limitations. Read more

RNP-1 - Ray-tracing simulation environment for RHS-based integrated communication and sensing networks

Ranplan Group AB (RNP), is seeking to appoint a high-calibre doctoral candidate to join the Marie Skłodowska-Curie Doctoral Network ‘joInt wireless commuNicaTion and sEnsinG by hologRaphic surfAce TranscEivers’ (INTEGRATE). Read more

Development of a Wireless Sensor for Measuring Water Storage in Glaciers

PROJECT OVERVIEW. An exciting opportunity to develop a new instrument to study water storage in glaciers. You should have either a background in engineering or environmental science, but with a keen enthusiasm to design, build and field-test an instrument that will need to work in a harsh environment. Read more

Development of broadband electronic warfare sensors for signal detection and direction finding

Who can apply? Australian & New Zealand Citizens. Industry partner and funding body SRC Aus Pty. Ltd. Defence Trailblazer. Program of study available Doctor of Philosophy (PhD) with the University of Adelaide. Read more

Human Interaction with Low-Speed Autonomous Vehicles

The University of York is embarking on ground-breaking research that focuses on data-centric engineering, digital twins, and AI, revolutionizing the way systems are designed and optimized through data. Read more

Semantic random-access technology for future wireless ecosystems

This PhD project will research into new technical innovations that can embrace today’s machine learning advances into a process of designing and managing wireless communications for emergent AI agents, where they will mimic human ability to effectively learn, fine-tune and adapt skills of conveying semantic information. Read more

Optimising dynamic scheduling in smart manufacturing through reinforcement learning PhD

This PhD aims to develop an adaptive self-organising solution for dynamic scheduling in job-shop manufacturing. The research will introduce an innovative approach that integrates deep reinforcement learning and multi-agent systems to rapidly respond to emergencies and disruptions. Read more

Learning for Control: Enabling Efficient Networked Autonomous Systems

Supervisory Team: Konstantinos Gatsis . Project description. There is an ongoing transformation in engineering autonomous systems that aim to achieve complex objectives with limited human intervention in applications such as robotics, self-driving cars, and industrial systems. Read more

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