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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 10 hours ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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scientists and build a workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML) methods to tackle complex
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of Government invite applications for Postdoctoral Fellowship to begin in August 2026. Supported by a grant from the National Endowment for the Humanities, this position advances the study of artificial
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:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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of technology, economy and our everyday life. Machines perform comparably to, or even surpass humans in playing board and computer games, driving cars, recognizing images, reading and comprehension. It is
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. Software or code development, incl. artificial intelligence and machine learning. Automation and robotics, incl. safe human-machine interaction. Serious gaming, incl. AR/VR. Life cycle analysis. You are
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& Managing CO₂ Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models to design and optimize the properties of materials. Conduct
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expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI