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cosmolgy, galaxy evoltion and stellar astrophysics. Students in my group primarily perform numerical simulations of stars, in order to study broad questions related to the origin of the elements in
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impact in translational fields, which often aim to use generative AI in a responsible way. This PhD project is part of a larger cohort of projects in the Monash AI Institute, a recently expanded program
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relevant fields of specialisation for this appointment are operations research, operations management, or a closely related discipline with strong computational and/or mathematical skills with expertise in
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). The reason for this is that the candidate will need to be trained in theories about humans and experimental methods. Meet H1E requirements for Monash FIT PhD entry.
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: ○ Where does geographical lack of data about the Birrarung make it hard to estimate its state? ○ How can we best supplement lack of data: by citizen science, new instrumentation, or modelling methods
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and experience in front-line customer service are required for success in this role. The successful candidate will have strong communication skills, demonstrated computer literacy and the ability
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people who discover them The Opportunity The Research Fellow will be a motivated and talented computational scientist and a key member of Monash University ice sheet modelling research team and SAEF’s
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sits at the forefront of an international program aimed at improving the understanding and treatment of alcohol use disorder. This position will leads functional neuroimaging research and plays a key
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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
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models (e.g. tumour progression, tumour-drug sensitivity, survivability) by integrating multiple and heterogeneous data with associative data mining and ensemble learning methods.