Publisher
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Cranfield University

PhD in AI and Machine Learning for Spectroscopic Greenhouse Gas Detection Cranfield University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Sponsored by EPSRC and Cranfield University. The studentship provides a tax-free bursary of up to £24,500 plus fees for three years; UK tuition fees are fully paid. Open to Home and Overseas fee status students, though only a limited number of Overseas studentships are available.

Deadline

Apr 6, 2027

Country flag

Country

United Kingdom

University

Cranfield University

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Keywords

Computer Science
Environmental Science
Signal Processing
Electrical Engineering
Laser Physics
Methane
Optical Sensor
Physics

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About this position

PhD opportunity at Cranfield University in the UK on AI and machine learning for spectroscopic greenhouse gas detection. The project sits at the intersection of computer science, physics, environmental science, and electrical engineering, with a strong focus on tunable diode laser spectroscopy, optical sensors, advanced signal processing, and data-driven methods for methane and greenhouse gas measurement.

You will work with a multidisciplinary team to develop and commercialise novel low-cost sensors, supported by EPSRC funding and collaboration with academic and industrial partners. The research includes building scientific understanding of sensor function and uncertainty, creating training data through replicable experiments, developing AI/ML-enabled models, and potentially carrying out field trials. The project also connects to the wider Rethinking Methane Measurement programme funded by ARIA.

Funding includes a tax-free bursary of up to £24,500 plus UK tuition fees fully paid for three years. The studentship is open to Home and Overseas fee status applicants, although only a limited number of Overseas studentships are available. Start date is listed as 06 Jun 2027, with flexibility possible by discussion with supervisors.

Entry requirements: a good degree (UK first or upper second class honours or equivalent) in physical science or engineering, with maths, basic coding, and practical work experience from your degree. Prior specialist AI experience is not required, but enthusiasm to learn and to apply new ideas is important.

Supervisors: Professor Jane Hodgkinson, Professor Weisi Guo, and Professor Ralph Tatam. Deadline: 06 Apr 2027. Apply via the online application form on the Cranfield University vacancy page.

Funding details

Sponsored by EPSRC and Cranfield University. The studentship provides a tax-free bursary of up to £24,500 plus fees for three years; UK tuition fees are fully paid. Open to Home and Overseas fee status students, though only a limited number of Overseas studentships are available.

What's required

Applicants should have a good degree (UK first or upper second class honours or equivalent) in physical science or engineering. Desired background includes maths, basic coding, and practical laboratory work. A willingness to learn, try new ideas, and tackle climate-change-related research is important; prior specialist AI skills are not required because training is provided.

How to apply

Complete the online application form for the studentship. Contact Professor Jane Hodgkinson by email if you need further information, and upload all required documents before the deadline. Early application is encouraged because the vacancy may be filled before closing.

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