457 web-programmer-developer-"https:"-"UCL"-"U.S"-"PhD-Jobs"-"https:" positions at Monash University
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, and their decisions can be confusing due to brittleness, there is a critical need to understand their behaviour, analyse the (potential) failures of the models (or the data used to train them), debug
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the Universe, e.g., where did the carbon in your bodies come from? What type of star made it? Generally we study stars in their final phases of evolution, when they become ageing red giants which is when
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model with each SNP independently, perhaps adjusting for other covariates such as age and sex. This project will focus on developing and applying novel machine learning and AI methods to improve
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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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for delivering high-quality lectures and tutorials, developing and updating course materials and academic research, conducting high-impact research in areas such as artificial intelligence, machine learning, cyber
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research community. This position is responsible for developing and maintaining a skilled team with strong technical expertise and a shared commitment to safe and ethical practice. It oversees quality
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catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon our groundbreaking research into the problem. Required knowledge A solid grounding in machine learning
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frameworks; develop the University’s long-term financial model; and embed best practice across budgeting, forecasting, scenario planning, research revenue reporting and analysis. This role will lead financial
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-term appointment Remuneration: The successful applicant will receive a tax-free stipend, at the current value of $36,063 per annum 2025 full-time rate, as per the Monash Research Training Program (RTP
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include: the evaluation of an existing health prevention program, the development of a measurement tool for health inequalities, behavioural experiments to assess how preventative interventions can improve