CDT in Earth observation: data for Earth systems - NERC

All enquiries relating to student recruitment should be directed to the Centre for Doctoral Training (CDT).

Number of notional studentships awarded: eight per year for three intakes, plus additional match-funded studentships.

Academic partners:

  • University of Edinburgh
  • University of Leeds (joint academic lead partners)
  • National Oceanography Centre
  • British Antarctic Survey.


The CDT in Earth observation: data for Earth systems was awarded to the Centre for Satellite Data in Environmental Science (SENSE) consortium.

Earth observation (EO) satellites collect hundreds of terabytes of data per day, with more collected from:

  • aircraft
  • drones
  • automated sensors.

However, due to a skills shortage only a fraction is analysed using the latest data science techniques, risking missed insights that could prevent or warn against environmental challenges.

This CDT will solve this through developing new scientists, uniquely trained in both EO techniques and advanced machine learning and artificial intelligence (AI) methods, to exploit data in multidisciplinary teams and make scientific breakthroughs.

NERC has invested about £2.2 million to support this CDT and academic and industry partners, to include the UK Space Agency, have committed to support additional training opportunities. The CDT will provide training between 2020 and 2026.

This CDT will support 50 PhD students funded by NERC and the CDT partners over three student intakes between 2020 and 2022.

Research areas and training

The CDT will offer training in the fields of data science, remote sensing, and environmental science. PhD studentships will include training in the following areas:

  • 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.

The aim of the CDT is for students to participate in a specially designed, comprehensive and innovative training programme. This will encourage their ability to work collaboratively, think creatively, and be comfortable in an academic and business environment.

This means that students will develop new insights and algorithms with real-world impact, and be prepared for careers in industry, government, academic and beyond.

Further information

Find out more about this CDT on the SENSE website, or by contacting the NERC Talent and Skills Team at

All enquiries relating to student recruitment should be directed to the CDT.

Last updated: 20 May 2022

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