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Field
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the design of innovative analytical and computational techniques to analyze,integrate and model multi modal data for the onset and progression of AMD. In doing so,the successful postdoctoral fellow will
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degree or equivalent in a related discipline. This project would suit individuals with academic or industrial experience in electronics, electrical engineering, systems engineering, or AI/data analytics
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for their projects. AI transformation processes in projects and organizations Ethical considerations of using AI in project planning and delivery The use of project data analytics in AI-driven decision-making Machine
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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bioinformatics Likelihood of advanced skills directly related to the research projects High level of analytical and problem-solving capability Ability to communicate complex information with clarity and to
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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analytical chemistry, mass spectrometry, or trace gas measurements is an asset Enthusiasm for laboratory and field work Willingness to engage in programming and data analysis (preferably Python) Excellent
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architectures, and on-device inference on edge-compute platforms. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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demonstrating how predictive analytics can improve maintenance and production planning. By comparing data-driven and traditional methods, the project will highlight the tangible benefits of digital platforms
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in Astronomy, Biology, Computer Science, Chemistry & Materials, Data Science & Scientific Computing, Earth Science, Mathematics, Neuroscience, and Physics in a world-class research environment