This PhD scholarship at the University of Newcastle offers an exciting opportunity to develop multimodal machine learning models for predicting treatment outcomes in glioblastoma patients, leveraging advanced imaging and clinical data. The project is embedded within the Brain Cancer Imaging Team, part of the School of Medicine & Public Health and the Hunter Medical Research Institute (HMRI), and is closely aligned with the Mark Hughes Foundation (MHF) Centre for Brain Cancer Research. The MHF has made a significant philanthropic commitment, enabling the establishment of a dedicated brain cancer research team led by Professor Michael Fay. The successful candidate will work under the co-supervision of Dr Nikitas Koussis, Dr Bryan Paton, Associate Professor Saadallah Ramadan, and Professor Michael Fay, contributing to a collaborative, interdisciplinary research environment focused on improving diagnostic accuracy and individualized therapeutic strategies through advanced MRI and machine learning. The project aims to design, implement, and validate a machine learning framework to predict post-operative and post-treatment clinical outcomes for patients undergoing neurosurgery and treatment for glioblastoma, one of the most aggressive forms of brain cancer. The research is conducted in partnership with John Hunter Hospital, providing access to real-world patient data and fostering close collaboration with clinical teams. The Imaging Centre is dedicated to integrating AI-driven tools into routine clinical workflows, setting new standards in brain cancer care and research. The scholarship provides a generous stipend of $37,440 per annum (2025 rate), tax free, for 3.5 years, indexed annually, along with a tuition fee scholarship and up to $1,500 relocation allowance. A stipend top-up may be negotiated. Applicants should have a strong interest in brain cancer imaging, willingness to execute research protocols and experimental design, ability to work in multidisciplinary environments, and motivation to advance clinical applications in brain cancer. The application process requires submission of an email expressing interest, academic transcripts, CV, a brief statement of research interests, and a proposal linked to the project. The deadline for applications is 17 November 2025. This position is ideal for candidates seeking to contribute to cutting-edge research at the intersection of medical science, computer science, and neuroscience, with direct impact on patient care and outcomes.