PhD studentship in Multimodal Generative AI for Embodied Collaborative Agents

Deadline: 31st January 2026 (or until the position is filled)

One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh.

The aim of this project is to develop multimodal generative AI for embodied collaborative agents. This project aims to create AI agents capable of seamlessly collaborating with humans and other agents in dynamic environments, utilising Vision, Language, and Action (VLA) models. The candidate will focus on designing novel training regimes and/or novel architectures for learning in embodied environments ranging from simulated environments (e.g., Web browsers, Videogames, etc.) to Robotics tasks.  

Candidate’s profile

  • A good Bachelors degree (2.1 or above or international equivalent) and/or Masters degree in a relevant subject (physics, mathematics, engineering, computer science, or related subject)
  • Proficiency in English (both oral and written)
  • A strong background in computer science, artificial intelligence, NLP, machine learning, or a related field
  • Experience with Python and Generative AI libraries (e.g., Huggingface Transformers)
  • Knowledge of Multimodal Generative AI models and their corresponding training methods is highly desirable

Studentship and eligibility

The School funded studentship starting in the academic year 2025/26 covers:

  • Full time PhD tuition fees for a student with a Home fee status (£5,006 per annum) and/or overseas fee status (£33,100 per annum)
  • A tax-free stipend of GBP £20,780 (subject to annual increment in line with UKRI rate) per year for 3.5 years

Application Information

Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: https://study.ed.ac.uk/programmes/postgraduate-research/491-informatics-ilcc-language-processing-speech-technology with a start date 14-09-2026 (home applicants).

Applicants should state “Multimodal Generative AI for Embodied Collaborative Agents” and the research supervisor (Alessandro Suglia) in their application and Research Proposal document. 

Complete applications submitted by 31st January 2026 will receive full consideration; after that date applications will be considered until the position is filled. The anticipated start date is 14-09-2026 but later start dates might need to be considered for international applicants needing to complete immigration processes before commencing their studies.

Applicants must submit:

  • All degree transcripts and certificates (and certified translations if applicable)
  • Evidence of English Language capability (where applicable)
  • A short research proposal (max 2 pages)
  • A full CV and cover letter describing your background, suitability for the PhD, and research interests (max 2 pages)
  • Two references (note that it the applicant’s responsibility to ensure reference letters are received before the deadline)

Only complete applications (i.e., those that are not missing the above documentation) will progress forward to Academic Selectors for further consideration. 

Environment

The Embodied, Situated, and Grounded Intelligence group works at the intersection between the Institute for Language, Cognition and Computation (ILCC) and the Institute of Perception, Action and Behaviour, ESGI is located at the School of Informatics of the University of Edinburgh, which provides a vibrant research environment and hosts several research institutes that are relevant to the research that the PhD student will be conducting. 

The School of Informatics is one of the largest in Europe and currently the top Informatics institute in the UK for research power, with 40% of its research outputs considered world-leading (top grade), and almost 50% considered top grade for societal impact. The University of Edinburgh is constantly ranked among the world’s top universities and is a highly international environment with several centres of excellence.