PhD: ML-Driven Video Wind Sensing for Site Hazards

European Geosciences Union (EGU); Loughborough; On-site; GBP 20,000 - 24,000; Full time

Benefits offered by this job

RTSG grant

Tuition fees covered

Job summary

Loughborough University invites applications for a PhD studentship exploring extreme winds using machine learning applied to video clips to better estimate site-specific wind hazard. The project runs 3.5 years from October 2027 with a tax-free stipend and tuition fees covered.

You will install cameras and anemometers, develop ML/video analysis pipelines, and link results to historical data to inform hazard mapping for potential national scale use.

Qualifications

• Master's degree in a relevant field or equivalent.
• Strong background in data analysis and ML is required.
• Experience with Python/R for scientific computing is preferred.

Responsibilities

• Set up a campus-scale living lab with cameras and anemometer sets for at least a year.
• Apply ML, computer vision and physics-based modelling to estimate wind gusts from video.
• Integrate video data with historical weather data (ERA5) and build a wind hazard map.

Skills

Machine learning

Image processing

Python

R

Fieldwork

Data analysis

Education

Master

Tools

Python

R

Job description

Loughborough University invites applications for a PhD studentship exploring extreme winds using machine learning applied to video clips to better estimate site-specific wind hazard. The project runs 3.5 years from October 2027 with a tax-free stipend and tuition fees covered.

You will install cameras and anemometers, develop ML/video analysis pipelines, and link results to historical data to inform hazard mapping for potential national scale use.