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engineering. Experience with experimental measurements, image-based diagnostics, laboratory testing or quantitative data analysis. Coding and analysis capability in Python and/or Julia, preferably with
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AI infrastructure. The Opportunity This is an unprecedented opportunity for an outstanding data science and AI PhD candidate interested in brain data analysis and AI, supervised by Dr Mahsa Salehi
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the next generation of personalised AI health coaching systems. Students will join a multidisciplinary PhD cohort spanning health, behavioural science, artificial intelligence, data science, and digital
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PhD Stipend Scholarship – Faculty of Medicine, Nursing and Health Sciences/Monash AI institute [AI-enabled personalised coaching for physical activity, sleep and health behaviour change] Job
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Expanding access to digital health The successful candidate will receive training in applied microeconometrics, health economics, environmental economics, discrete choice experiments, administrative data
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PhD scholarship opportunity in Materials Science and Engineering: NOₓ production by plasma bubble reactor Job No.: 697669 Faculty/Portfolio: Faculty of Engineering Location: CSIRO Clayton, Victoria
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collaborators have recently been awarded an Incorporating Patient Data in Health Technology Decision Making Grant under the 2025 Preventative and Public Health Research Initiative of the Medical Research Future
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able to transfer to a PhD, subject to academic performance and approval. Degrees and application information Admission requirements and how to apply: www.monash.edu/engineering/future-students/graduate
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● Electrical and Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering For further information, please follow the link for each Graduate Research Degree ● 3291
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such as data science, mathematical statistics, actuarial science or public health or psychology with strong statistical training. For full information on eligibility and English language requirements