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of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug
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. Delegating lab tasks to ensure deadlines are met. Reporting to PI regularly on key metrics (including budgets) for priority projects. The successful candidate must have: a PhD degree in biology, biomedical
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: · Education: PhD in Materials Science or similar. Knowledge in tech transfer will be highly valuable. · Knowledge: Advanced materials development Polymeric materials development, functionalization
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: · Education: PhD in Materials Science or similar. Knowledge in tech transfer will be highly valuable. · Knowledge: Advanced materials development Polymeric materials development, functionalization
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and energy saving for the smart urban built environment, etc.) Hydrogen energy Fuel cell/flow battery Waste water treatment Energy economics, policy and security, environmental and social impacts
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models that are more efficient, inherently multimodal, and capable of processing information at an unprecedented scale. Key research questions include (but not limited to): Non-Autoregressive and Diffusion
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, such as biology, chemistry, physics, neuroscience, applied physics, data science, bioengineering, chemical engineering, computer science, electrical engineering, materials science, neurology
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-class research hub dedicated to fundamental materials physics, advanced technologies, and industrial manufacturing implementation frameworks.By driving breakthroughs in material science assisted with data
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Biomedical Engineering Search Committee. Please be advised that only shortlisted candidates will be notified of the result of the application. (Information provided by applicants will be used for recruitment
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reasoning skills and attention to details, allowing you to carry out rigorous science Ability to progressively develop a strategy to extract novelty from the data and your results Organizational skills