We are recruiting for a Research Fellow to join our on a full-time, fixed-term until 31st March 2028, basis to work on The Learning from Collaborative Storytelling project. The Learning from Collaborative Storytelling project is an EPSRC-funded research programme that brings together interdisciplinary expertise from computer vision, cognitive robotics, and human-robot interaction. The project is led by the School of Computing, Engineering, and the Built Environment at Edinburgh Napier University, with collaboration from academic partners and industry stakeholders. The ambitious programme aims to create a new framework for visual scene understanding through interactive, collaborative storytelling between humans and robots. By integrating multimodal data, advanced computer vision techniques, and cognitive models, the project seeks to enhance robots' ability to acquire a deeper contextual understanding of dynamic environments and to support real-world applications in education, healthcare, and assistive technology. Duties
* Undertake high-impact research in developing and evaluating real-time machine learning models for visual scene understanding and collaborative storytelling between humans and robots. Priority research areas include knowledge extraction from visual data (e.g., image and video streams), multimodal interaction for contextual reasoning, and real-time narrative generation. Of particular interest are models that integrate cognitive robotics and multimodal data sources to enhance robots' ability to engage in meaningful dialogue.
* Design and implement experimental protocols for data collection and human-robot interaction studies. This includes setting up laboratory and real-world evaluations, coordinating collaborative storytelling activities, and analysing results using both quantitative and qualitative data analysis techniques.
* Contribute to the development and evaluation of cognitive frameworks that integrate commonsense knowledge and real-world sensory input for improved understanding and interaction in diverse environments.
* Prepare high-quality, peer-reviewed publications for leading journals and conferences and disseminate research findings at national and international conferences.
PhD degree in a relevant field (Computer Vision, Robotics, Conversational AI, Multimodal Interaction).
* Excellent programming skills in Python and/or C++, with expertise in deep learning frameworks (e.g., PyTorch, TensorFlow).
* A strong background in computer vision, cognitive robotics, machine learning, multimodal interaction, or a related area.
* Research experience in visual scene understanding, human-robot interaction, natural language processing/generation, or multimodal storytelling systems.
* A strong publication record in top-tier international journals and conferences (e.g., CVPR, ICRA, HRI).
* Experience in developing and evaluating real-time algorithms for complex visual data analysis and interactive multimodal systems.
* Strong quantitative research skills
The Schools of Computing and Engineering & the Built Environment have around 200 academics, 3,100 campus-based students, and deliver programmes with professional accreditations from the British Computer Society, Institution of Engineering and Technology, The Chartered Institute of Building and other accreditation bodies. We have excellent computing, engineering and construction lab facilities.
The School of Computing is highly regarded and one of the UK's largest computer science departments. The School of Engineering & the Built Environment houses leading UK research centres in transport policy and sustainable construction. The schools are based in the lively and exciting Merchiston area at the heart of Edinburgh, Scotland's inspiring capital. The University's improved research power rating will now see our research funding increase as we take significant strides to grow our reputation as a research-focused institution as well as a teaching one. We are confident that we are well on our way to establishing ourselves as one of the UK's world-leading universities in research. £36,924 per annum