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methodologies Experience with machine learning techniques Experience with pipeline development and testing (gitlab, simulated light curves…) Ability to work independently and to collaborate in an international
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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, etc.). Required Qualifications* PhD in medical physics, nuclear engineering or other engineering or physics disciplines. Applicants with medical degrees with relevant experience will also be considered
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participation in the war in Myanmar since the 2021 military coup d’état. This responsibility includes a mapping of the conflict’s digital war ecology and focusing in on a specific example of remote participation
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experience in using statistical and mathematical tools to analyse and interpret soil data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python
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classification for conducting cutting-edge and life-changing research that creates impact in our communities. Additionally, for more than a decade, they have received a national Military Friendly® School
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of extrusion systems, reinforcement strategies, construction detailing, and construction scale experiments. RA3) Machine Learning and Optimisation for Digital Construction: Data-driven and simulation-based
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: Essential criteria A doctorate (or will shortly satisfy the requirements of a PhD). The doctorate must be in a relevant discipline area, such as statistical machine learning, computational and quantitative
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and