Research Assistant

Overview

Queen Mary University of London is seeking a Research Assistant to join the School of Engineering and Materials Science for the Self-Learning AI Recipe Engine project. Working in collaboration with an agri-tech industry partner, the project investigates the application of artificial intelligence, computer vision, and reinforcement learning to optimize growing conditions within indoor vertical farming. The successful candidate will work under the supervision of Dr M Hasan Shaheed on a full-time, fixed-term 12-month position based on site in the United Kingdom.

Who can apply

Candidates must hold an MSc in Artificial Intelligence, Machine Learning, Computer Science, Data Science, or a closely related subject. Applicants need to have some experience working with machine learning in Python, ideally utilizing tools such as PyTorch or TensorFlow, along with an interest in applying artificial intelligence to real-world challenges. Beneficial qualifications include prior experience with computer vision, image analysis, dataset preparation, data handling, model performance evaluation, and statistical analysis techniques. Experience involving reinforcement learning, sensor data, or agricultural AI applications is considered an advantage but is not strictly required.

What you get

The position provides a salary ranging from £39,187 to £39,802 per annum. Benefits include access to a pension scheme, 30 days of annual leave on a pro-rata basis for fixed-term contracts, a season ticket loan scheme, and professional development opportunities. Additional provisions encompass inclusive employment policies, flexible working arrangements, campus facilities, and reasonable recruitment adjustments for candidates with disabilities.

Requirements

The role requires preparing and labelling datasets, supporting the training and evaluation of computer vision models for tasks such as plant growth monitoring, and assisting with reinforcement learning models that recommend growing conditions. The responsibilities also include contributing to experimental trials at the industry partner growing facility, analyzing results, and supporting the preparation of research publications.

Key dates

The closing date for applications is 2026-11-20.