At a Glance
- Tasks: Develop AI-powered remote sensing technologies for environmental monitoring and landscape change.
- Company: Cranfield University, a leader in technology and management education.
- Benefits: Competitive salary, flexible working options, and opportunities for impactful research.
- Other info: Dynamic research environment with excellent career growth and collaboration opportunities.
- Why this job: Join an innovative team and contribute to cutting-edge environmental research.
- Qualifications: PhD in relevant fields and experience with deep learning and remote sensing.
The predicted salary is between 46492 - 46492 £ per year.
Faculty of Engineering and Applied Sciences is seeking a Research Fellow in Remote Sensing and AI on a Fixed Term Contract for 18 months, or until project end date (whichever is sooner). The 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.
About the Role
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.
About You
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 such as PyTorch and possess strong Python programming skills. Experience working with Remote Sensing datasets and geospatial technologies such as GDAL or RioXarray 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.
About Us
Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. 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 at scale.
Our Values and Commitments
Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. 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.
Working Arrangements
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.
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