Rashid Kamal

Two fully funded PhD positions are available in the research team of Rashid Kamal, Lecturer (Assistant Professor) at Ulster University, UK. The projects are situated at the intersection of Artificial Intelligence and Healthcare, with a focus on addressing real-world challenges such as clinician burnout and wearable device security. The first project, 'Securing Medical IoT,' aims to develop lightweight and trustworthy AI solutions to protect sensitive data on medical devices like smartwatches and glucose monitors. The second project, 'Clinical Form Automation,' focuses on building agentic NLP models and large language models (LLMs) to automate clinical paperwork, enabling doctors to dedicate more time to patient care. The support package for these positions includes full tuition fee coverage and a tax-free stipend of £19,237 per year. Additionally, successful candidates will have the opportunity to gain paid experience as a Lab Demonstrator for up to 6 hours per week. International applicants are welcome and encouraged to apply. Applicants should have a strong background in computer science, artificial intelligence, or related fields, with an interest or experience in healthcare applications, medical IoT, or natural language processing. The research group is committed to developing AI that delivers tangible benefits in real-world healthcare settings. For more information and to apply, visit the provided application link. The research is based at Ulster University, a leading institution in the UK, and is supervised by Rashid Kamal. This is an excellent opportunity for motivated researchers to contribute to impactful AI and healthcare projects.

Ulster University is advertising a fully funded PhD opportunity in the School of Computing on Secure AI for Healthcare Digital Twins . The project sits at the intersection of computer science , cybersecurity , artificial intelligence , digital health , and medical science . It focuses on privacy-preserving federated learning, secure synthetic data generation, and adversarial machine learning for healthcare applications such as personalized medicine and remote patient monitoring. This PhD aims to develop a trustworthy secure AI framework that protects sensitive medical data while enabling robust model training and resilience against cyber threats. The post explicitly says the position is fully funded and open to both national and international students . Ideal applicants should be highly motivated and interested in AI, secure machine learning, and healthcare innovation. No specific deadline, stipend amount, or language-test waiver is mentioned in the post. To apply, read the full details via the linked application page and follow the instructions there.