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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
. Education: We prepare tomorrow`s healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented
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strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics
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learning, understand their mathematical foundations, and connect them to space-related technologies and missions. The focus is on building rigorous models that explain and predict the behaviour of modern
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the research group, University and broader research community. Curious to learn more? Don’t hesitate to contact us. The team The successful candidate will work as part of the Photonic Materials & Optical Fibres
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motivated by combining rigorous modelling with direct industrial impact in the green transition. You have: A PhD in chemical engineering, process engineering, mechanical engineering, data science, computer
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-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data
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that can be repurposed for viruses with pandemic potential. This includes working closely with computer scientists to utilize published “omics” datasets and machine learning approaches to identify FDA
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networks, from a machine learning and information theory perspective. This basic research project has strong translational potential and aims to elucidate how immune function is altered during sepsis, with
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for the Zilverstand lab in the Department of Psychiatry and Behavioral Sciences. Anna Zilverstand, PhD, is an Associate Professor in Psychiatry and the lab Principal Investigator. The lab is part of the University
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to that mission. We will award up to four postdoctoral fellowships to our 2027-28 cohort. PIIRS seeks recent PhDs in the Social Sciences who have demonstrated exceptional scholarship, congruent with the Institute's