661 computational-physics "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Monash University
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have a different application process – or none at all. Read the application details carefully and submit your application by the deadline. For more details, visit our scholarships application page.
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Monash Mentor Scholarships The Monash Mentor Scholarship is designed to recognise excellence of students participating in the Access Monash Mentoring program. Mentors have the opportunity to develop
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an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled 'Reasonable Adjustments Request' for a
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work...
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure Advisory System, or data from other implantable or wearable devices. This involves consideration of both...
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We have several PhD opportunities available in areas such as Multimodal Large Language Models (MLLM) for human understanding, MLLM safety, and Generative AI. If you have published in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, etc.), you will have a strong chance of receiving a full...
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operational and safety functions of our Physical Containment Level 2 (PC2) laboratory facilities. PC2 labs are designed for work with moderate-risk biological materials that require controlled access
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large, culturally diverse undergraduate and postgraduate cohorts, and maintain an active program of research and scholarly activity. The Department of Management is a diverse, inclusive group committed
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cutting-edge AI methodologies, focusing on combining data-driven approaches with physics-informed models to tackle challenges in MRI reconstruction. By integrating MRI acquisition physics directly into
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, containerisation (Docker), and basic bioinformatics pipelines will be preferred. Cross-disciplinary training and co-supervision with computational and neuroscience partners under GEMS 2026 will be provided. Project