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Profile PhD in Computer Science, Data Science, Machine Learning, Engineering, Biomedical Informatics, Bioengineering, or a related field Proficiency in python programming Strong expertise in machine
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. Project background Wearable technologies that analyze non-conventional biological matrices, such as interstitial fluid, promise longitudinal biomarker data with minimal invasiveness. These provide insights
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learning, XR, robotics or other technologies - to enhance processes across the entire value chain of new construction or renovation projects. Potential topics may include, but are not limited to: Data-driven
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. Contribute to grant writing and proposals to secure additional funding. Mentor graduate and undergraduate students, as appropriate. Profile PhD in Computer Science, Data Science, Machine Learning, Engineering
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interdisciplinary teams, including material scientists, physical chemists and computational material modelers Prepare manuscripts, reports, and presentations to disseminate findings Profile Qualification PhD in
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material modelers Prepare manuscripts, reports, and presentations to disseminate findings Profile Qualification PhD in chemical/process engineering, materials science, chemistry or closely related field
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position is part of a larger consortium bringing together engineering, data science, microbiology and medical expertise from ETH Zürich, University Zürich and Balgrist Hospital. Job description Design