Research Assistant in AI-Enabled Species Mapping
Research Assistant in AI-Enabled Species Mapping role at The University of Sheffield
Overview
The University of Sheffield is seeking a motivated research assistant to join the FORGE project (Forest Governance through AI-enabled Evaluation of Species Mapping in the Peruvian Amazon). The project investigates how artificial intelligence and remote sensing can enhance the monitoring of tropical forests affected by illegal and unsustainable logging.
The postholder will contribute to evaluating AI-based image segmentation algorithms capable of recognising both common and rare tree species in highly-diverse ecosystems such as the Peruvian Amazon. Working with drone-based imagery and validated field data, the research assistant will help assess the accuracy, robustness and operational value of these algorithms for large-scale forest inventories and the detection of endangered species. The successful candidate will collaborate closely with OSINFOR, the Peruvian authority responsible for supervising forest concessions, to ensure that research outputs address practical challenges in biodiversity monitoring and enforcement of international conservation agreements such as CITES.
Key Responsibilities
* Build and train initial AI models for canopy delineation and species identification.
* Conduct an early evaluation of model performance.
* Compute model confidence levels.
* Develop a QGIS plugin or Python GUI‑Tool.
* Support the writing of the technical report with results and finalise dissemination outputs.
* Prepare a proof‑of‑concept paper.
* Attend meetings with Sheffield and OSINFOR teams.
* Carry out other duties commensurate with the grade and remit of the post.
Qualifications
Essential:
* Good honours degree (or equivalent) in computer science, engineering, remote sensing or a related discipline.
* Demonstrated experience in programming, preferably in Python, and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
* Knowledge of computer vision or image analysis methods, including segmentation or classification techniques.
* Good written and verbal communication skills, including the ability to contribute to technical reports and academic publications.
* Familiarity with version control systems (e.g., Git/GitHub) for collaborative software development.
* Ability to work independently and as part of a collaborative team.
* Good problem‑solving and critical‑thinking skills.
* Familiarity with basic experimental evaluation and data analysis (e.g., plotting results, interpreting experimental outcomes).
Desirable (if applicable):
* Interest in environmental sustainability or biodiversity conservation.
Person Specification
Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.
Salary & Working Arrangement
Salary: £32,080 to £33,951 pro‑rata (equivalent to a full‑time salary), with an actual salary of £19,248 to £20,371 per annum based on 21 hours a week.
Working arrangement: Part‑time. Duration: 1st May to 31st July 2026. Line manager: Lecturer in Computer Vision (project lead). Direct reports: None.
Benefits
* Minimum of 38 days annual leave including bank holiday and closure days (pro‑rata) with the ability to purchase more.
* Flexible working opportunities, including hybrid working for some roles.
* Generous pension scheme.
* Wide range of discounts and rewards on shopping, eating out and travel.
* Stellar staff networks providing opportunities for social interaction, peer support and personal development (Race Equality, LGBT+, Women’s and Parent’s networks).
* Recognition Awards to reward staff who go above and beyond in their role.
* A commitment to your development, access to learning and mentoring schemes.
* Family‑friendly policies: paid time off for parenting and caring emergencies; support for those going through menopause; paid time off and support for fertility treatment; and more.
Recruitment Process
The selection process will consist of a presentation and an interview. The university will let candidates know if they have progressed to the selection stage in the week commencing 2nd February 2026, and the selection will take place at least a week after the invitation. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process, you can contact the Computer Science Recruitment Team at COM-Recruitment@sheffield.ac.uk.
Contact
For informal enquiries about this job contact Dr Jefersson A dos Santos, project lead, at J.Santos@sheffield.ac.uk.
Legal and Equality Statement
We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process. We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision (https://www.sheffield.ac.uk/vision) outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.
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