George De Ath
4 months ago
This scholarship has expired. You can find similar scholarships from the section below or browse our scholarships listing pages.
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
United Kingdom
University
University of Exeter

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Meet Kite AI
Ongoing programEPSRC and NATS Funded PhD Studentship
by Engineering and Physical Sciences Research Council (EPSRC) and NATS, in partnership with the University of Exeter
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.
Explore the programSuggested scholarships
Keywords
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.
Ask ApplyKite AI
Professors

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.