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neuroscientists pursuing advanced research and development in neuromorphic computing, artificial intelligence, and spiking neural networks across a range of applications. A strong background in theory (e.g
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Smart Damage Sensing, Sustainability and Green Energy Production), a multidisciplinary research program combining polymer chemistry, functional materials, photocatalysis, artificial intelligence, and high
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Classification Title: Post-Doctoral Associate in Philosophy and Ethics of Artificial Intelligence Classification Minimum Requirements: A PhD in Philosophy, Computer Science, or another AI-related
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of artificial intelligence and robotics. The postdoctoral researcher actively participates in the research, teaching and administration of this group. Further information can be found here: https
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description The Center of Interdisciplinary Data Science and Artificial Intelligence (CIDSAI) at NYU Abu
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in probabilistic temporal event dynamics. Required Qualifications: - PhD in computer science, engineering, biomedical data science, informatics with advantage for experience in conducting research
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are looking for candidates to have the following skills and experience: Essential criteria 1. PhD qualified in a relevant subject area, such as theoretical physics, computational physics, quantum information
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of ORNL researchers with various backgrounds (e.g., material science, neutron science, chemistry, manufacturing, computing, others). Interact and collaborate with researchers from universities, national
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. Computing and analysis – Illustrator, Powerpoint, Excel, Word, ImageJ, HTML 9. Documentation – daily record of work performed in files and laboratory notebook Scholarship: 10% 10. Contribute data and ideas
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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