59 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions at Monash University
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qualitative research. This project aims to develop a scalable EEG foundation model capable of learning general-purpose representations of brain activity that can support diverse neurotechnology and multimodal
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PhD Scholarship Opportunity - Developing the Next Generation of Evidence-Based Rheumatology Researchers Job No: 698225 Location: Monash University School of Public Health and Preventative Medicine
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Australian adults experience these financial support systems. These insights will be utilised to co-design a navigation support model that can assist individuals in accessing and engaging with these systems
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lists. We engage with industry and other world leading institutes to carry out pioneering research that benefits society and changes the world around us. Our world-class researchers are driven by a
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and other world leading institutes to carry out pioneering research that benefits society and changes the world around us. Our world-class researchers are driven by a passion and commitment to leaving a
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for infrastructure platforms in minerals-to-green metals transformation. It will suit a candidate interested in combining experimental materials science, advanced characterisation, and data-driven modelling to develop
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. The Opportunity This interdisciplinary PhD project between IT and the social sciences will explore the development of computational approaches for detecting and analysing misogynistic backlash ecosystems across
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interventions. Potential research activities include: Developing prediction models for receptivity and lapse Conducting micro-randomised or n-of-1 trials Evaluating psychological mechanisms of engagement and
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protoplanetary discs matched to our nearest star-forming regions* Modelling outbursts in young stars during star cluster formation* Modelling how dust grows from micron-sized grains to km-sized planetesimals in
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, spectroscopy, astrometry) using massive optical telescopes on Earth and in space (e.g., Hubble, Gaia, JWST, Kepler, TESS). My group develops cutting-edge models to extract the most from noisy data and to better