638 assistant-professor-computer-science-"https:"-"https:"-"https:"-"https:" positions at Monash University in Australia
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis methods. In this work we study the effects putative NMDA antagonists xenon, a potent anaesthetic, and...
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Relevant bibliography: - Chades, I., Carwardine, J., Martin, T., Nicol, S., Sabbadin, R., & Buffet, O. (2012). MOMDPs: a solution for modelling adaptive management problems. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 26, No. 1, pp. 267-273). - Blau, T., Bonilla, E....
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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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evaluation Applications of AI in biomedical research This project is suitable for students with an interest in genetics, computational biology, or data science. A background in statistics, computer science
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My interests span a wide range of topics in theoretical physics, including: geometric phases, topological defects in matter and radiation fields, inverse problems (scalar and vector tomography), singular optics, using electrons, atoms and light and the exploration of complex systems using...
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Modern map-based systems and location-based services rely heavily on the ability to efficiently provide navigation services and the capability to search points of interests (POIs) based on their location or textual information. The aim of this project is to build a next-generation navigation...
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value Up to $6,000 Number offered One See details Bachelor of Medical Science and Doctor of Medicine Imogen This scholarship has contributed to my achievement of publishing my first paper as
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Future Fund–supported program (2026–2030) to strengthen evidence on addiction, self-harm and mental ill health. The multidisciplinary study will analyse 20 years of binational cohort and cross-sectional
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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...