Graduate Teaching Assistantship

This fully funded PhD position at Sheffield Hallam University offers an exciting opportunity to work at the intersection of artificial intelligence, privacy, robotics, and mental health. Hosted by the College of Business, Technology and Engineering, and based in the Department of Computing and Informatics, the project is part of the Graduate Teaching Assistantship (GTA) scheme. The successful candidate will contribute up to 180 hours per year to teaching or research support, in addition to pursuing their doctoral research.

The research aims to develop a privacy-preserving, AI-based large language model (LLM) system for detecting anxiety and depression in care robotics. The project addresses critical challenges in healthcare AI, including trustworthiness, privacy, and clinical validation, especially when handling sensitive mental-health data. The system will feature a role-based privacy framework, ensuring secure and ethical interactions for patients, clinicians, and caregivers. Methodologically, the project involves fine-tuning lightweight LLMs (e.g., GPT4All-LoRA) on ethically sourced mental-health datasets, implementing GDPR-compliant privacy architectures, and deploying solutions on advanced robotic platforms and embedded systems such as Care-O-Bot and Nvidia Jetson.

Applicants should have at least a 1st or 2:1 Honours degree in AI, Cybersecurity, or a related discipline. Strong analytical, technical, and communication skills are essential. International applicants must meet English language requirements (IELTS 7, minimum 6.5 in all areas, or equivalent, taken within the last two years). Applications from underrepresented groups are strongly encouraged.

The GTA scholarship covers tuition fees (UK and international) and provides a maintenance bursary of £22,152 (2025/26) for 3.5 years. The application deadline is 7 May 2026. To apply, submit an online application with a tailored personal statement, CV, two references, degree certificate and transcript, and, if applicable, IELTS results and passport copy. For more information and to apply, visit the project page.