Research Associate in Computer Vision and Environmental Modelling

University of Sheffield; Sheffield; Hybrid; GBP 38,000 - 46,000; Full time

Benefits offered by this job

Flexible working

High-performance computing access

GPU facilities

Job summary

The University of Sheffield invites applications for a Research Associate to join the Next-Generation Forest Inventory (NextGen-FI) project. You will develop AI and remote sensing methods for forest monitoring and illegal logging detection, combining computer vision, deep learning, and geospatial analysis.

You will translate research into practical tools, including a QGIS plugin, validate algorithms on UAV imagery, and work across data processing, model development, validation and deployment in

Qualifications

• PhD required in computer science or related discipline.
• Candidates from GIS, remote sensing or ecology are welcome.

Responsibilities

• Develop and evaluate deep learning frameworks for spatio-spectral-temporal UAV imagery.
• Investigate uncertainty-aware and incremental learning methods for robust mapping.
• Translate research into practical tools, including a QGIS plugin for forest monitoring.
• Validate algorithms using UAV imagery and work across data processing, model development, validation and deployment.

Skills

Computer vision

Deep learning

Remote sensing

Geospatial analysis

UAV imagery processing

Education

PhD in computer science

PhD in GIS/remote sensing/ecology

Tools

Python

QGIS

PyTorch

Job description

Applications are invited for a Research Associate to join the Next-Generation Forest Inventory (NextGen-FI) project, developing advanced artificial intelligence and remote sensing methods for forest monitoring and the detection of illegal logging.

The successful candidate will undertake research at the intersection of computer vision, deep learning, remote sensing and geospatial analysis, working closely with academic and stakeholder partners.

The project addresses the challenge of automated tree species mapping in highly diverse forests, where species and conditions encountered in practice may not have been represented during model training. The project will investigate open-set recognition approaches to enable AI systems to recognise known species while identifying and appropriately handling previously unseen classes.

The postholder will develop and evaluate deep learning frameworks for spatio-spectral-temporal UAV imagery, exploring foundation models and multimodal learning approaches. They will also investigate uncertainty-aware and incremental learning methods to improve the robustness and adaptability of tree species mapping systems.

The role will involve translating research into practical tools, including contributing to the development of a QGIS plugin for forest monitoring and validating algorithms using UAV imagery. The postholder will work across the research pipeline, from data processing and model development to validation and deployment.

The role is based in the Computer Vision Lab (PRISMA Team) within the School of Computer Science at the University of Sheffield, with access to high-performance computing and GPU facilities. The postholder will work closely with researchers from the Schools of Geography & Planning and Biosciences, as well as with academic and stakeholder partners, contributing to an interdisciplinary programme spanning AI, machine learning, remote sensing, geospatial analysis, ecology and forest conservation.

Applicants should hold a PhD in computer science or a related discipline. Candidates from GIS, remote sensing or ecology are also welcome, particularly those with relevant experience in UAV data processing, remote sensing, machine learning and/or computer vision.

The School of Computer Science at the University of Sheffield is a world-leading centre for research and education in computer science and artificial intelligence. We are committed to exploring flexible working opportunities which benefit the individual and University.

The University of Sheffield is a remarkable and inclusive place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.