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PhD Studentship: Machine learning and AI for air traffic control, Computer Science – PhD (EPSRC and NATS Funded).

University of Exeter

The always-on, safety-critical nature of air traffic control raises rich and exciting challenges for machine learning and AI. The University of Exeter in partnership with NATS, the UK’s main air navigation services provider, has established the Centre for Doctoral Training in Air Traffic Management pioneering new research in machine learning and AI for air traffic control. During their first year, this cohort of funded students will receive training in machine learning and AI methods at the University, together...

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The always-on, safety-critical nature of air traffic control raises rich and exciting challenges for machine learning and AI. The University of Exeter in partnership with NATS, the UK’s main air navigation services provider, has established the Centre for Doctoral Training in Air Traffic Management pioneering new research in machine learning and AI for air traffic control. During their first year, this cohort of funded students will receive training in machine learning and AI methods at the University, together...

Opportunity details

The always-on, safety-critical nature of air traffic control raises rich and exciting challenges for machine learning and AI. The University of Exeter in partnership with NATS, the UK’s main air navigation services provider, has established the Centre for Doctoral Training in Air Traffic Management pioneering new research in machine learning and AI for air traffic control. During their first year, this cohort of funded students will receive training in machine learning and AI methods at the University, together with training in the fundamentals of air traffic control at NATS, based at Whiteley on the south coast. In addition to this training, in the first year students will undertake two shorter research projects before determining their main research topic in conjunction with academic and industry supervisors. A wide variety of PhD projects is available; example project areas are: Human-machine teaming AI agents for air traffic control Weak signal analysis for air traffic control room situational awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep learning, AI, cognitive science, uncertainty quantification, probabilistic methods are encouraged to apply. For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. Students will be based at the Streatham Campus in Exeter with funded visits to NATS. The studentship will be awarded on the basis of merit. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuit...

Eligibility

For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee (~£24k) and stipend. International applicants should to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.

Requirements

For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee (~£24k) and stipend. International applicants should to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.

Funding and benefits

Funding eligibility: UK Students, EU Students, International Students, Self-funded Students. Funding amount: UK tuition fees and an annual tax-free stipend of at least £21,805 per year.

How to apply

Students with interests in machine learning, deep learning, AI, cognitive science, uncertainty quantification, probabilistic methods are encouraged to apply. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee (~£24k) and stipend. This means there are special terms that apply to the project, these will be discussed with candidates at interview and fully set out in the offer letter.

Open the official application information

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Host country/countriesUnited Kingdom
Eligible countries/nationalitiesAll nationalities
Study levelPhD / Doctorate
Field of studyBusiness, Computer Science, Artificial Intelligence
Funding typeFully funded
DeadlineSep 25, 2026
Academic year/intakeNot stated
Application feeCheck provider details.

Source and verification

Check the current official call before applying

Recorded source check: September 22, 2026. A stored check date does not guarantee that every field is complete or still current. Compare the provider, eligibility, funding and deadline with the live official call before applying.

Open source: www.jobs.ac.uk

Benefits

Funding eligibility: UK Students, EU Students, International Students, Self-funded Students. Funding amount: UK tuition fees and an annual tax-free stipend of at least £21,805 per year.

Eligibility summary

For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee (~£24k) and stipend. International applicants should to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.

Requirements

For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £21,805 for 4 years full-time, or pro rata for part-time study. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee (~£24k) and stipend. International applicants should to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.

Documents required

Not stated. Verify with the provider.

Language/test requirements

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Listing-board disclaimer

Prime Scholarship Alerts is an independent listing board, not the scholarship provider, university or funder. We do not select applicants, collect provider application fees or guarantee an award. Verify requirements, deadlines, funding, fees and application instructions through the current provider page before applying.

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