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scans and use advanced data-driven methods, including artificial intelligence (AI) and machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology
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technology, computer-aided design, microfabrication and ‑fluidics, culture of human cells, analytical cell and molecular biology techniques, and bioimaging methods. Analytical and proactive – You combine sharp
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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trajectories? Passionate about archival research and oral history? Self-motivated and ready to learn new research skills? The Department of History is looking for two PhD candidates to undertake archival and
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engineering or a closely related field. Hands-on expertise – You have experience with OoC or MPS technology, computer-aided design, microfabrication and ‑fluidics, culture of human cells, analytical cell and