Research Assistant (AI Learning)

Research at Edinburgh Napier University’s School of Computing, Engineering and Built Environment (SCEBE) is recognised as world leading or internationally excellent in UK’s REF. The latest UK national research assessment (REF 2021) places our computer science as third best in terms of research power in Scotland.

Currently, we are undertaking an EPSRC-funded project titled “Learning from Collaborative Storytelling” (LoCS) which aims to explore how robots can learn about the world through interactive storytelling with humans.  As such, we are recruiting a Research Assistant to play a central role in designing models, prototypes, and experimental studies that will help to drive progress and influence the direction of this high-profile project.

The Role:

As Research Assistant on the LoCS project, you will be in an excellent position to use knowledge gained through your Master’s degree in a closely relevant field (e.g. Robotics, Conversational AI, Natural Language Processing, or Multimodal Interaction) to contribute to real research innovation: building multimodal perception and dialogue modules, shaping experimental pipelines, and working with real robot platforms.

Your experience in machine learning model development and strong programming skills (using Python and/or C++) will allow you to effectively take technical ownership of key project components, including developing and refining machine learning models for multimodal perception, spoken dialogue, or narrative generation.

Having practical experience with Large Language Models (LLMs), including prompt engineering, fine-tuning, safety-aware adaptation, or integrating LLMs into interactive systems will also serve you well, as you develop robust prototypes that integrate visual understanding, emotion recognition, and dialogue systems into functional robotic behaviours, working closely with the PI and senior researchers to conduct advanced analysis of multimodal datasets, applying deep learning, statistical modelling, or machine learning techniques to extract insights and improve system performance.

The role offers excellent progression opportunities for those considering a future PhD and provides hands-on experience in publishing research with guidance from senior researchers.

If you have the appropriate skills and experience and would like to take part in this rare opportunity to work on cutting-edge, multimodal AI that will directly advance the next generation of human–robot interaction, then we would love to hear from you.

What we will need from you:

• Master’s degree in a closely relevant field (e.g. Robotics, Conversational AI, Natural Language Processing, or Multimodal Interaction)
• Strong programming skills in Python (and/or C++), with experience using deep learning frameworks such as PyTorch or TensorFlow
• Hands-on experience developing or adapting Vision-Language Models (VLMs) for tasks such as scene understanding, grounding, or multimodal fusion.
• Ability to design, run, and evaluate experiments involving multimodal datasets or user interaction.
• Excellent interpersonal skills, with the ability to engage and communicate effectively with academic colleagues, students, and external collaborators.

Benefits we offer:

Pension with employer contributions of 17.6% - 26% and a minimum of 46 days holiday per annum. Professional development opportunities, discounted access to onsite sports facilities and a wide range of other staff discounts. For more information about our wide range of benefits, click here.

Additional information:

Contract: Fixed term – 24 months, Full time – 35 hours per week

Interviews: Week commencing 12^th January 2026

Applications will be reviewed on a rolling basis, so we encourage you to apply as soon as possible.

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