Job Description
Job Title:  Research Assistant in AI-Enabled Species Mapping
Posting Start Date:  19/12/2025
Job Id:  1934
School/Department:  Computer Science
Work Arrangement:  Part Time (Hybrid)
Contract Type:  Fixed-term
Salary per annum (£):  £32,080 - £33,951 (pro-rata)
Closing Date:  18/1/2026

The University of Sheffield is a remarkable 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.

We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more. Find out more about our benefits (opens in a new window) and join us to become part of something special.

 

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 include data preparation and analysis, experimental evaluation of AI models, preparation of visual and written reports, and contribution to academic publications. The post offers an opportunity to apply computer vision and remote sensing methods to pressing environmental issues and to work within an international, interdisciplinary team.

 

Applicants should hold a good honours degree (or equivalent) in computer science, engineering, or a related field, with strong programming skills in Python and familiarity with machine learning or image analysis. An interest in environmental sustainability or biodiversity conservation is highly desirable.

 

 

Main duties and 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

 

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.

 

Criteria

Essential or desirable

Stage(s) assessed at

A good honours degree (or equivalent) in computer science, engineering, remote sensing, or a related discipline.

Essential

Application/interview

Demonstrated experience in programming, preferably in Python, and familiarity with deep learning frameworks such as PyTorch or TensorFlow.

Essential

Application/interview

Knowledge of computer vision or image analysis methods, including segmentation or classification techniques.

Essential

Application/interview

Good written and verbal communication skills, including the ability to contribute to technical reports and academic publications.

Essential

Application/interview

Familiarity with version control systems (eg Git/GitHub) for collaborative software development.

Essential

Application/interview

Ability to work independently and as part of a collaborative team.

Essential

Interview

Good problem-solving and critical-thinking skills.

Essential

Interview

Familiarity with basic experimental evaluation and data analysis (e.g., plotting results, interpreting experimental outcomes).

Essential

Interview

 

Further Information

 

Grade

Grade 6

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.

Work arrangement

Part-time

Duration

1st May to 31st July 2026

Line manager

Lecturer in Computer Vision (project lead)

Direct reports

None

Our website

sheffield.ac.uk/cs/research/groups/computer-vision

For informal enquiries about this job contact Dr Jefersson A dos Santos, project lead, at J.Santos@sheffield.ac.uk  

 

 

Next steps in the recruitment process

The selection process will consist of a presentation and an interview. We plan to 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

 

 

Our vision and strategic plan

We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window).

What we offer

  • A 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.
  • A wide range of discounts and rewards on shopping, eating out and travel.
  • A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, 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.
  • A range of generous family-friendly policies
    • paid time off for parenting and caring emergencies
    • support for those going through the menopause
    • paid time off and support for fertility treatment
    • and more


More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).

 

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 (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.

Disability Confident Leader