David Coomes
Top university
1 month ago
Postdoctoral Research Associate in Nature Restoration, Computer Science, and Remote Sensing at University of Cambridge University of Cambridge in United Kingdom
Degree Level
Postdoc
Field of study
Computer Science
Funding
This is a 3-year fixed-term, fully funded postdoctoral research associate position at the University of Cambridge. Details on salary and benefits are available on the official job posting.
Country
United Kingdom
University
University of Cambridge

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About this position
The University of Cambridge is offering a 3-year Postdoctoral Research Associate position focused on nature restoration, computer science, remote sensing, and ecology. The successful candidate will join a dynamic team led by Professor David Coomes, Professor of Forest Ecology and Conservation. This role centers on the TESSERA project, an innovative open, global geospatial foundation model that utilizes self-supervised learning on multi-sensor satellite time series data. The model produces 10 m embeddings for applications such as land cover mapping, crop classification, and canopy height estimation.
The position provides an exciting opportunity to co-design research projects aligned with the candidate's interests, working at the intersection of environmental science and advanced computational methods. Applicants should have a PhD in a relevant field, with expertise in geospatial data, remote sensing, and machine learning. The University of Cambridge offers a collaborative research environment and full funding for the duration of the post.
Interested candidates should apply promptly, as the application window closes in less than a week. For more information and to apply, visit the official job posting. This position is ideal for researchers passionate about leveraging technology for environmental impact and advancing the field of nature restoration.
Funding details
This is a 3-year fixed-term, fully funded postdoctoral research associate position at the University of Cambridge. Details on salary and benefits are available on the official job posting.
What's required
Applicants should have a PhD in a relevant field such as environmental science, computer science, remote sensing, or ecology. Experience with geospatial data, self-supervised learning, and satellite imagery analysis is highly desirable. A strong publication record and the ability to work collaboratively are preferred.
How to apply
Visit the provided application link to review the full job description and submit your application. Ensure your materials highlight relevant expertise. Apply before the deadline as there is less than a week left.
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