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Sources: The William S. Reese ‘77 Digital Cultural Heritage Postdoctoral Program Yale University Library Innovation Fund Teaching Responsibilities: None Compensation and benefits: https://postdocs.yale.edu
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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that leverage state-of-the-art AI methods (deep learning, generative AI, Bayesian modelling, active learning, etc.) to combine cellular imaging data, chemical compound structure, viral genomes and other omics
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Job Posting Title: Postdoctoral Fellow, AI Healthcare Innovation ---- Hiring Department: Quantitative and Systems Health Science (QSHS) ---- Position Open To: All Applicants ---- Weekly Scheduled
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, Wallumattagal Campus, North Ryde About the Fellowship The China Strategic Knowledge Initiative at Macquarie University invites applications for a full-time Postdoctoral Research Fellowship commencing in 2027
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Memorial Sloan-Kettering Cancer Center | New York City, New York | United States | about 2 months ago
Experience in high-dimensional data analysis Preferably have a deep learning or foundation models for biomedical data. Submit C.V., cover letter, and 3 references in your application submission to: Contact
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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/recruitment/2-year-postdoctoral-p… ** Project ** Computational and high field MRI characterization of learning and decision-making ** Supervisor and contact ** Dr Florent MEYNIEL https://www.unicog.org/lab
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | about 2 months ago
. The candidate will join ongoing projects in our team and perform mathematical/computational modeling. The topics include (1) constructing deep learning-based models to predict the molecular microenvironments
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, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in