PhD Studentship: AI Active EMI Filters at University College London 2025-2026

This project explores the use of AI-based methods, particularly reinforcement learning and neural-network-driven control, to develop adaptive active EMI filters (AEFs) that can sense, classify, and suppress EMI in real time across dynamic conditions. The candidate will design, simulate, and experimentally validate intelligent filtering systems that respond autonomously to EMI fluctuations. Working closely with Jaguar Land Rover, the student will have access to real-world electric drivetrain testbeds and system-level EMC data. The project will also investigate the trade-offs between filter performance, system complexity, and real-time feasibility. The outcomes of this research are expected to improve the reliability and sustainability of future electric vehicles, while advancing the integration of AI into safety-critical electronic systems. As part of the PhD, the candidate will engage with industrial engineers, participate in EMI testing campaigns, and contribute to the development of the next generation of intelligent powertrain platforms.

Table of Content

• Summary
• Benefits
• Requirements
• Interview Process
• Application Deadline
• How To Apply

Summary

• Application DeadlineNot Specified
• Study LevelPhD
• SponsorUniversity College London
• City to studyLondon
• School to studyUniversity College London
• Course to studyArtificial Intelligence (AI) , Artificial Intelligence and Adaptive Systems , Civil and Environmental Engineering , Civil Engineering , Environmental Engineering , Geomatic Engineering
• Eligible CountryAll Countries

Benefits

Fully funded 4-year PhD studentship covering international fees, with a £20,198 per annum tax free stipend in Year 1, rising with inflation.

Requirements

Essential Criteria:

• A first-class or high 2:1 honours degree (or equivalent) in Electrical Engineering, Electronic Engineering, Computer Engineering, or a related discipline.
• Strong foundation in one or more of the following:
• Electromagnetic compatibility (EMC) or interference (EMI)
• Power electronics or analogue/digital circuit design
• Machine learning, reinforcement learning, or AI control
• Proficient in at least one technical computing language (e.g., Python, MATLAB, Simulink, or C++).
• Ability to work independently and collaboratively in interdisciplinary teams.
• Excellent written and verbal communication skills.

Desirable Criteria:

• Master’s degree (or equivalent industrial experience) in a relevant field.
• Experience with EMI testing, active filter design, or real-time embedded control.
• Familiarity with model-based design, signal processing, or control systems engineering.
• Experience in working with automotive systems or industrial electronics.
• Interest in applied research and working with industry partners.

Applications are welcome from candidates with a broad interest in sustainable technologies and AI-enabled electronic systems, and a strong motivation to contribute to impactful industrial research.

Selection Process

Review of applications will start from September 1, 2025.

Application Deadline

How To Apply

• Applicants should apply through (https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/civil-environmental-and-geomatic-engineering-mphil-phd) and include
  • a letter of motivation,
  • CV
  • research proposal of no more than 1,000 words (excluding bibliography).
    • In the proposal, please describe the research questions and objectives, proposed methods and data, and potential choice of case studies.

For more details, visit UCL Scholarship webpage