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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
teaching at the college or university level, with experience in data science, artificial intelligence, or a related field. * Knowledge of artificial intelligence and machine learning concepts, including
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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on large-scale numerical simulations, instrumented experiments, and onboard robotic data could learn generic representations of local interactions between mobile robots and their environment, enabling
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 1 hour ago
. or Diploma in bioinformatics or a comparable qualification Extensive programming experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image
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. Large and deep AI models can be built using these data sets and machine learning, which can be combined with real-time satellite-based AIS data and sensors such as radar and algorithms for anomaly
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on machine learning and networks, release the code in open access and actively participate in the international interpretability community. Where to apply Website https://seuelectronica.upc.edu/en/procedures
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
concepts into accessible, domain-relevant learning experiences for students. The full job description is available here: https://computing.mit.edu/lecturer/ Job Requirements REQUIRED: PhD in Computer Science
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Responsibilities: Conduct project related research on geophysical/geomechanical investigation, geomodelling, data analytics, and machine learning. Responsible for processing and analyzing geophysical/geomechanical
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Environmental Engineering (CEE). For more information, please visit: https://earthobservatory.sg , https://ntu.edu.sg/ase , and https://ntu.edu.sg/cee . We are looking to fill a total of 5 Research Fellow