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fundamental research. The students willing to learn about IP management, create patents of their works, and translate research from lab-to-industry are encouraged to apply. At the end of the PhD, the student
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The scholarship is associated with developing a Digital Twin-Driven model in mass production for Ford Motor Company. The scholarship is associated with developing a Digital Twin-Driven model in mass production for Ford Motor Company. 3 Years 3 Years One (1). One (1). Australian Permanent...
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Future Fellowship project Unifying discrete and continuous methods in quantum information theory . Your focus will be on producing high-quality research in mathematical quantum physics, contributing
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and conduct laboratory experiments to optimise geopolymer formulations. Experience with durability testing methods and mechanical property evaluation of cementitious materials. The selected candidate
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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. Specialist knowledge of Indigenous led studies of Indigenous culture, art, sustainability, regenerative futures, and/or community. 4. Demonstrated experience of HASS research methods and planning, including
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. Mandatory Qualifications For the Level A Industry Research Assistant: Qualification in the relevant discipline area preferably at postgraduate level For the Level B Industry Research Fellow: PhD or equivalent
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and to produce high quality outputs. To be successful in this position, you will have: PhD or equivalent in relevant field. Demonstrated capability involving nanomaterials formulation (preferably lipid
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analysis. Interdisciplinary collaboration. Critical thinking. Qualifications and requirements The candidate should have a PhD in a topic relevant to regeneration and a track record of undertaking and
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this position, you will have: PhD degree in relevant field Demonstrated knowledge of structural analysis of alloy components, Finite Element Modelling (FEM) and preferably morphology/topology optimisation