632 computational-physics-"https:"-"https:"-"https:"-"https:"-"BioData" positions at Monash University
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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications based on electronic medical records. It is also attractive for novel applications, e.g. multimodal...
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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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, 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
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Australian permanent resident Australian humanitarian visa holder You must meet the following criteria: A student commencing a Botanical Sciences Honours Program in the Faculty of Science at a Monash campus in
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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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I supervise a wide range of projects in stellar astrophysics, with a focus on low and intermediate-mass stars, which have masses similar to or slightly larger than our Sun. This work is carried out within the Centre of Excellence for Astrophysics in 3D: ASTRO 3D. As a member of my group, you...
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will interact with Australian and international researchers in the fields of solid-state physics, materials science and nanotechnology, gaining state-of-the-art expertise in these areas of research. "2D
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are committed to fostering 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
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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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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available at one time. In non-stationary environments on the other hand, the same algorithms cannot be applied...