| Location: | Bristol |
|---|---|
| Salary: | £43,482 to £50,253 per annum pro rata, Grade: J/Pathway 2 |
| Hours: | Part Time |
| Contract Type: | Permanent |
| Placed On: | 11th March 2026 |
|---|---|
| Closes: | 25th March 2026 |
| Job Ref: | ACAD108505 |
The role
We are seeking a Senior Research Associate (Grade J, 0.4 FTE, fixed-term for 12 months) to join the School of Geographical Sciences at the University of Bristol on a newly awarded UKRI Smart Data Research Fellowship. The project will develop the UK’s first national-scale geospatial framework to map, quantify and optimise perennial energy crops, supporting decarbonisation and sustainable land-use planning. The successful candidate will play a leading technical role in developing advanced geospatial and AI-based models for high-resolution crop detection, biomass estimation and spatial suitability analysis.
Working closely with the Principal Investigator, the postholder will design and implement scalable data-processing pipelines integrating aerial imagery, LiDAR and satellite datasets, and contribute to the development of robust, reproducible machine learning workflows. The role forms part of a nationally significant research programme with strong policy relevance, working in collaboration with the Imago Data Service and external stakeholders. The position offers an exciting opportunity to contribute technical leadership within an interdisciplinary research environment and to produce high-impact publications, open datasets and decision-support tools that support the UK’s green transition.
What will you be doing?
You will lead the technical development of geospatial and AI-based approaches to map and quantify perennial energy crops across the UK. This will involve designing and implementing scalable data-processing pipelines using very high-resolution aerial imagery, LiDAR and satellite datasets, and developing robust machine learning models for crop detection, biomass estimation and spatial suitability analysis.
You will contribute to methodological innovation in multimodal data fusion and uncertainty quantification, ensuring that models are reproducible, transparent and suitable for national-scale application. You will work closely with the Principal Investigator to translate research outputs into open datasets and decision-support tools with direct policy relevance.
The role will also involve contributing to high-quality academic publications and conference presentations, engaging in collaborative discussions within the research team, and participating in stakeholder-facing activities associated with the Fellowship. You may provide informal technical guidance to junior researchers or postgraduate students contributing to the project.
You should apply if
You are comfortable working with large-scale datasets such as high-resolution imagery, LiDAR or satellite time series, and can build reproducible data pipelines using Python and modern deep learning frameworks. You enjoy solving complex methodological challenges and translating technical models into meaningful environmental or policy-relevant insights.
You are motivated by working at the interface of AI and sustainability, and are keen to contribute to a nationally significant research programme with real-world impact. You are able to work independently, communicate clearly within interdisciplinary teams, and take ownership of technical delivery within a fixed-term project.
Additional information
Contract type: Open ended with fixed funding for 1 year
Work pattern: 14 hours per week/40% time
This advert will close at 23:59 UK time on 25/03/26
For informal queries please contact: Dr Ce Zhang, Senior Lecturer in Environmental Data Science Tel: +44 117 456 0163 Email: ce.zhang@bristol.ac.uk
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