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We have 9 atmospheric monitoring PhD Projects, Programmes & Scholarships

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atmospheric monitoring PhD Projects, Programmes & Scholarships

We have 9 atmospheric monitoring PhD Projects, Programmes & Scholarships

Measuring wind on Mars using orbital imaging data

These projects are open to students worldwide, but have no funding attached. Therefore, the successful applicant will be expected to fund tuition fees at the relevant level (home or international) and any applicable additional research costs. Read more

Water quality monitoring and forecasting through integration of geospatial and remotely sensed data

How can geospatial data from diverse sources, such as satellites, Uncrewed Aerial Vehicles (UAVs), and Uncrewed Surface Vehicles (USVs), be combined to effectively map, monitor, and predict pollution in freshwater and coastal ecosystems?. Read more

Advancing Earth Observation with Artificial Intelligence

  Research Group: Bradford-Renduchintala Centre for Space AI
The integration of Artificial Intelligence (AI) with Earth Observation (EO) offers transformative possibilities for advancing environmental monitoring, resource management, and disaster preparedness. Read more

AI to the rescue of climate change, modelling air quality for cleaner urban planning

  Research Group: Computing, Informatics and Applications Research Group
Research Group. Computing, Informatics and Applications Research Group. Proposed supervisory team. Dr Lakshmi Babu Saheer. Dr Javad Zarrin. Read more

Unravelling past dryland hydroclimate (RS25/EE/GES/MARKOWSKA)

Our planet's drylands are at the centre of an intriguing climate mystery. These regions, which cover nearly half of Earth's land surface and support 2 billion people, are predicted to expand significantly as our planet warms. Read more
Last chance to apply

Superminiaturised sensor for space weather measurements

A novel energetic particle detector has been developed, using a small scintillator crystal to both count particles and determine their energy. Read more

Data-Centric Solutions for Earth Observation Challenges: Developing Cutting-Edge Techniques for Remote Sensing Analysis [SELF-FUNDED STUDENTS ONLY]

In today's data-driven landscape, the importance of data-centric machine learning methodologies cannot be overstated where they prioritize the quality, diversity, and accessibility of data, recognizing that the performance and reliability of machine learning models heavily depend on the data they are trained on. Read more
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