QMUL - TME PhD Studentship 2025 (CLOSED)

About the Project

 

This fully funded PhD studentship, supported by Toyota Motor Europe (TME), will be hosted at the Centre for Multimodal AI and the Multimedia and Vision (MMV) Group at Queen Mary University of London (QMUL), UK. The project will be supervised by Dr. Dimitrios Kollias, Assistant Professor in AI.

This PhD project aims to design and develop novel, holistic, context-aware, robust, and trustworthy multimodal AI and machine/deep learning models for the detection and interpretation of emotional and affective states in real-world, unconstrained settings (i.e., in-the-wild).

Understanding human behavior and affect is a complex task, influenced by a wide range of factors including emotion, cultural background, and situational context. This complexity is further compounded by the presence of noisy or biased data, which can reduce model accuracy, and by the opaque nature of many deep learning models, which lack interpretability. Furthermore, models trained on limited or homogenous datasets often struggle to generalize across diverse populations and environments.

This project will address these challenges by advancing research in the following key areas:

2.  Context Awareness – enabling models to interpret affective states with an understanding of contextual factors.

3.  Fairness, Explainability, and Ethics – ensuring models are transparent, unbiased, and ethically aligned.

4.  Generative AI and Personalization – leveraging generative models to create adaptive, personalized affective computing systems.

Start Date:

September 2025

 

Duration:
 3.5 years (with an additional 0.5 years for thesis writing and submission)

 

 

Team Collaboration

 

This PhD project offers a unique opportunity to work in a highly collaborative and interdisciplinary environment. The candidate will be part of a dynamic team at the Centre for Multimodal AI and the Multimedia and Vision (MMV) Group at Queen Mary University of London (QMUL), UK. The project is supported by Toyota Motor Europe (TME), providing an excellent blend of academic and industrial collaboration.

The supervising team includes:

·      Dr Dimitrios Kollias (QMUL)

·      Dr Hazem Abdelkawy (TME)

 

The candidate will have the opportunity to collaborate with experts from various fields, including AI, machine learning, and affective computing. This interdisciplinary approach will enhance the research experience and provide a broader perspective on the project's challenges and solutions. Additionally, the candidate will benefit from the industrial insights and resources provided by TME, ensuring that the research has real-world applications and impact, such as deployment and evaluation within vehicle or robotics testing environments.

 

Funding
 This PhD studentship is fully funded for both UK and international candidates and includes:

·   A tax-free stipend at the UKRI London rate (~£23,000 for 2024 - 2025)

·   Full tuition fee waiver (Home or Overseas rate)

·   Support for research expenses, including conference travel

·   Engaging in a collaborative and innovative research environment (industrial collaboration with Toyota Motor Europe and academic mentorship at QMUL)

·   The chance to work on cutting-edge research and a high-impact project with potential for real-world deployment and patenting

·   Access to state-of-the-art computing resources and facilities (GPUs, HPC clusters) and personalized mentorship.

 

Candidate Profile & Requirements:
 National and international applicants should have:

·   A Master's degree (or be close to completion) in Electronic Engineering, Computer Science, or a related discipline

·   A First-Class or Distinction degree is highly desirable

·   Strong background in AI, machine learning, and/or deep learning

·   Experience in Python and deep learning libraries/frameworks such as PyTorch and TensorFlow

·   Prior research experience or publications in relevant fields are highly desirable

·   Excellent problem-solving, communication (both written and verbal), and collaboration skills and a passion for research

·   For non-native English speakers: a minimum IELTS score of 6.5 overall, with 6.0 in writing, or equivalent qualification

 

Closing Date

20th June 2025. Application review will start after that time.

 

 

How to apply

 

Please send the following documents in a single email to Dr. Dimitrios Kollias at d.kollias@qmul.ac.uk:

·   CV

·   Motivation letter

·   Academic transcripts

·   Names and contact details of two referees

 

Contact email

d.kollias@qmul.ac.uk