Publisher
source

George De Ath

6 months ago

EPSRC and NATS Funded PhD Studentship

PhD in Machine Learning and AI for Air Traffic Control at the University of Exeter University of Exeter in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Four PhD studentships are available. Eligible home students receive full home tuition fees and an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. International students may apply, but the award only covers part of the international tuition fee (around £24k) plus stipend, so they must cover the remaining tuition and additional costs. Funding includes training at the University of Exeter and NATS, plus funded visits to NATS.

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Exeter

Ongoing program

EPSRC and NATS Funded PhD Studentship

by Engineering and Physical Sciences Research Council (EPSRC) and NATS, in partnership with the University of Exeter

Partially Funded
PhD
4 Years Full-time
United Kingdom

Industry-linked PhD studentships at the University of Exeter in Machine Learning and AI for Air Traffic Control, supported by EPSRC and NATS. Funding is full for eligible home students and partial for international students.

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Keywords

Computer Science
Machine Learning
Cognitive Science
Electrical Engineering
Deep Learning
Mathematics
Artificial Intelligence
Uncertainty Analysis
Air Traffic Management

About this position

Applications are open for a second cohort of PhD studentships in Machine Learning and AI for Air Traffic Control at the University of Exeter, in partnership with NATS. This is a research-focused doctoral opportunity in areas such as human-machine teaming, AI agents, decision support for controllers, and weak-signal analysis for air traffic control room situational awareness.

The project sits within the University of Exeter’s Centre for Doctoral Training in Air Traffic Management and combines academic supervision with industry-linked training. Students will spend the first year receiving training in machine learning and AI methods at Exeter and in air traffic control fundamentals at NATS, with funded visits to NATS during the programme.

Funding: 4 studentships are available. Eligible home students receive full home tuition fees and an annual tax-free stipend of at least £21,805 for 4 years full-time (or pro rata for part-time study). International applicants are welcome, but the award only covers part of the international tuition fee and stipend, so they must cover the remaining tuition and additional costs such as visa and healthcare surcharge.

Eligibility: Applicants should have, or be about to obtain, a First or Upper Second Class UK Honours degree (or equivalent) in Computer Science, Mathematics, Engineering, or Cognitive Science. Interest in machine learning, deep learning, AI, uncertainty quantification, or probabilistic methods is encouraged. Non-native English speakers must meet the English language requirements and provide proof of proficiency.

Deadline: midnight BST on 6 May 2026. Interviews are expected in the week commencing 18 May 2026. Successful applicants must be able to start in September 2026.

How to apply: Apply through the University of Exeter portal, upload the required documents, and quote reference 5855. The application requires a CV, letter of application, transcripts, two referees’ names, and English language evidence if applicable.

Funding details

Four PhD studentships are available. Eligible home students receive full home tuition fees and an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. International students may apply, but the award only covers part of the international tuition fee (around £24k) plus stipend, so they must cover the remaining tuition and additional costs. Funding includes training at the University of Exeter and NATS, plus funded visits to NATS.

What's required

Applicants must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree or equivalent in an appropriate area of Computer Science, Mathematics, Engineering, or Cognitive Science. Candidates should have an interest in machine learning, deep learning, AI, cognitive science, uncertainty quantification, or probabilistic methods. If English is not the applicant’s first language, they must meet the English language requirements and provide proof of proficiency. International applicants are eligible, but they should be able to cover the remaining international tuition fee, visa, healthcare surcharge, and relocation costs.

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Professors

Professor

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Mathematics

Machine Learning

Uncertainty Analysis

Air Traffic Management

Professor

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Cognitive Science

Electrical Engineering

Mathematics

Computer Science

Professor

University Name
Country flag

United Kingdom

Research Interests

Statistics

Health Economics

Uncertainty Analysis

Disease Modeling

Reproducibility

Professor

University Name
Country flag

United Kingdom

Research Interests

Statistics

Artificial Intelligence

Computer Science

Applied Mathematic

Data Science

Professor

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Deep Learning

Uncertainty Analysis

Machine Learning

Electrical Engineering