199 structural-engineering-"https:"-"https:"-"https:"-"https:"-"https:"-"Fraunhofer-Gesellschaft" positions at Monash University
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the eligibility criteria above. This scholarship is open to those conducting research within the faculties of Arts (School of Music only); Engineering; Medicine, Nursing and Health Sciences and Science. How
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to access leadership and community engagement opportunities and to support the development of emerging engineering leaders to encourage these talented individuals to enter the mining industry upon completion
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discover them The Opportunity Monash University’s SensiLab, a world-leading research facility at the intersection of creative practice and advanced technology, is seeking an innovative and forward-thinking
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with
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Short description The PhD project is focused on recommended design and engineering principles of totally renewable microgrids with the ambition to outperform traditional networks reliability
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In many branches of science (e.g., Artificial Intelligence, Engineering etc.), the modelling of the problem is done through the use of functions (e.g., f(x) = y). On a very high-level, we can think
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innovative tools including 3D cardiac organoids, engineered heart tissues, and CRISPR technologies, with the ultimate goal of identifying targeted therapies that can change lives. Learn more about ARMI Key
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atmosphere models Strong background in mathematics, physics, engineering or related field Experience in scientific computing, including C/C++, fortran, python, or MATLAB Version control and package management
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in conventional imaging, and to access a complementary ‘dark-field’ signal that originates from tiny sample structures. We do this by designing and implementing novel experimental set-ups and
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with