This Earth Observation CDT is an exciting new centre funded by the Natural Environment Research Council and the UK Space Agency, that will train 50 PhD students to tackle cross-disciplinary environmental problems, by applying state-of-the-art data science methods to the deluge of satellite data collected each day. Our graduates will be supervised by a consortium of world-leading UK scientists, with topics co-developed with the UK’s most innovative spatial data companies. By training a new generation of industry-experienced satellite data specialists we will support the growing strategic importance of remote sensing within the UK space sector, and enhance the UK’s profile as an international leader in Earth Observation science.
It aims to create a:
- Internationally renowned centre for research training in Earth Observation and data science techniques, and their application to Earth system challenges.
- Bonded cohort of self-supporting students, with strong mentoring across years, sites and disciplines.
- Multi-disciplinary training environment with graduates that have the skills and ambition to innovate and become future Earth Observation leaders.
- Open and collaborative partnerships between academia and industry, which stimulates exploitation of satellite data and seeds new research ideas.
- Happy, diverse and inclusive research environment that leads the way on widening participation.
- New satellite datasets and techniques that will delivering a meaningful legacy to the UK through careers in industry, NGOs, government and academia.
The research conducted by these new NERC Earth Observation PhD studentships covers a range of thematic areas, including:
- Atmospheric science, composition, and meteorology
- Land and sea ice cryosphere research
- Monitoring the ocean temperature, sea state, dynamic ocean topography
- Land cover change
- Forestry, burnt area, and biomass
- EO data assimilation into climate models
- Combining Earth Observation datasets with advanced computer techniques, such as AI, neural networks, and machine learning