Research Fellow in Remote Sensing and AI

Organisation/Company Cranfield University Department HR & Development Group Research Field Environmental science » Other Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2) Positions PhD Positions Final date to receive applications 17 Sep 2026 - 00:00 (Europe/London) Country United Kingdom Type of Contract Temporary Job Status Full-time Hours Per Week 37 Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme Reference Number 5381 Is the Job related to staff position within a Research Infrastructure? No

Faculty of Engineering and Applied Sciences

Environmental Sustainability

Research Fellow in Remote Sensing and AI

Fixed Term Contract for 18 months, or until project end date (whichever is sooner)

Full time starting salary is normally in the range of £38,655 to £46,492 per annum

Location:
Cranfield, Bedfordshire

We welcome applications from passionate, talented, and dedicated individuals to help develop the next generation of AI-powered remote sensing technologies for monitoring landscape change and environmental sustainability at scale.

We are seeking an ambitious Postdoctoral Researcher to join the Landscape Observatory at Cranfield, an exciting research initiative developing advanced Remote Sensing and Artificial Intelligence capabilities for environmental monitoring. You will develop and apply state-of-the-art deep learning methods for land cover classification and change detection using multi-source aerial and satellite imagery. Working within an interdisciplinary team and supported by cutting-edge HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at major scientific conferences.

You will be educated to doctoral level in Remote Sensing, Geography, Geoinformatics, Computer Science, Artificial Intelligence, Machine Learning or a related discipline. You will have experience developing deep learning models using frameworks using PyTorch and possess strong Python programming skills. Experience working with Remote Sensing datasets and geospatial technologies such as GDAL or Rio Xarray is essential. You should have knowledge of semantic segmentation, time-series analysis and modern AI approaches together with a developing publication record appropriate to your career stage.

Experience with High-Performance Computing (HPC) clusters, geospatial foundation models, large-scale geospatial processing or cloud-based Earth Observation platforms would be advantageous.

You will be a highly motivated researcher with strong analytical and problem-solving skills, excellent communication abilities and a passion for delivering impactful environmental research.

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here .

The role will be based within Cranfield Environment Centre, which undertakes internationally recognised research focused on understanding and managing environmental change through the integration of environmental science, remote sensing, artificial intelligence, systems modelling and data science. Through initiatives such as the Landscape Observatory, the Centre develops innovative solutions that support environmental monitoring and decision-making ther information is available at:
Cranfield Environment Centre.

Our shared, stated values help to define who we are and underpin everything we do:
Ambition;
Impact;
Respect; and Community. Find out more here .

We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families . Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here .

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.

Closing date for receipt of applications: 17 September 2026