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engineering applied mathematics civil engineering geotechnical engineering applied physics other related disciplines. Demonstrated knowledge or experience in any of the following: computational fluid dynamics
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discipline) Science or applied science Mathematics or data science Computer science Environmental or sustainability studies Design, manufacturing, or technology fields Applicants should demonstrate: A strong
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degree (honours) or master degree by research in either: mechanical engineering biomedical engineering chemical engineering civil engineering applied mathematics applied physics related disciplines
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PhD in the epidemiology field Eligibility criteria Undergraduate degree with Honours or Masters in Science with units in mathematics and/or biostatistics Demonstrated coding experience: either
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. At least one degree should be geodesy/surveying, mathematics, physics, engineering or related course. Additionally, the applicant should preferably have experience in: research and programming skills in
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English language requirements. Completion of a bachelor (honours) degree or master degree by research in: civil engineering geotechnical engineering petroleum engineering mechanical engineering applied mathematics
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Be part of a pioneering centre that's setting the global standard for responsible AI Shape the future of technology while making a meaningful impact on society Join a collaborative environment where
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information, please contact: Professor Dennis Petrie dennis.petrie@monash.edu or Dr Gozde Aydin gozde.aydin@monash.edu Integrated PhD Program The project is based in the Centre for Health Economics (CHE), a
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Resources Engineering, Hydrology/Hydraulics, Environmental Science, Remote Sensing or a related field. Someone with previous training in computer modelling and coding, or with demonstrated experience in field
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from other quantitative disciplines – such as data science, mathematical statistics, actuarial science, public health, or psychology – who have strong quantitative skills and an interest in causal