University Of Exter Machine Learning & AI for Air Traffic Control PhD Studentship (Stipend £20,780 per year)

The University of Exeter, in collaboration with NATS (the UK’s leading air navigation service provider), has launched a pioneering Centre for Doctoral Training. This program is designed to solve high-stakes, safety-critical challenges in aviation using cutting-edge Artificial Intelligence.

Dec 30, 2025 - 10:22
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University Of Exter Machine Learning & AI for Air Traffic Control PhD Studentship (Stipend £20,780 per year)
University Of Exter Machine Learning & AI for Air Traffic Control PhD Studentship (Stipend £20,780 per year)

The University of Exeter, in collaboration with NATS (the UK’s leading air navigation service provider), has launched a pioneering Centre for Doctoral Training. This program is designed to solve high-stakes, safety-critical challenges in aviation using cutting-edge Artificial Intelligence.

Financial Support & Funding Package

This is a fully-funded studentship designed to support researchers for the long term.

  • Annual Tax-Free Stipend: At least £20,780 per year.

  • Tuition Fees: Full coverage of Home/UK tuition fees.

  • Duration: 4 years of full-time funding (pro-rata for part-time).

  • Placement: Based at the Streatham Campus, Exeter, with funded industry visits to NATS in Whiteley.

The First Year: Training & Exploration

Unlike traditional PhDs, this program offers a foundational first year to bridge the gap between AI and Aviation:

  1. Dual Training: Master ML/AI methods at the University while learning the fundamentals of Air Traffic Control at NATS.

  2. Mini-Projects: Complete two short research rotations before finalizing your main PhD thesis topic.

  3. Mentorship: Benefit from dual supervision by academic professors and industry experts from NATS.

Potential Research Areas

Candidates can choose from a variety of innovative projects, such as:

  • Human-Machine Teaming: Optimizing how AI agents and human controllers work together.

  • AI Agents: Developing autonomous systems for traffic management.

  • Signal Analysis: Using AI to detect "weak signals" for better situational awareness in control rooms.

Candidate Profile

Eligible Backgrounds:

  • Computer Science, Mathematics, Engineering, or Cognitive Science.

  • Strong interest in Machine Learning, Deep Learning, Probabilistic Methods, and Uncertainty Quantification.

Eligibility Note: Funding is primarily for students with Home/UK fee status. If you have moved to/from the UK or ROI within the past 3 years, eligibility advice should be sought.

Application Details & Deadlines

  • Job Reference: 5518

  • Closing Date: January 11, 2026

  • Placement Date: Posted on December 23, 2025

  • Selection: This studentship is awarded strictly on the basis of Merit.

Industry Partnership: Because NATS provides funding and material support, special terms apply to the project. These will be detailed during the interview and in the formal offer letter.

VISIT OFFICIAL PAGE TO APPLY

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