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breakthrough and to contribute to the welfare of society and humanity through developing innovative technologies. We also conduct research on ethical, legal and social issues caused by the spread of AI
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, complex systems. Strong communication and writing skills; ability to work both independently and as part of a team. About the team The DATA team develops foundational mathematical and algorithmic approaches
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 27 days ago
computationally intensive, relying on iterative time-marching algorithms to reconstruct heating environments. This limits their use in more advanced computational analyses, such as uncertainty quantification
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Responsibilities The appointee will join a multidisciplinary team led by the Principal Investigator to develop AI‐driven navigation systems in robotic implant surgery. The duties include but not limited
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict
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in our team. Learn more about us here: https://sc.cs.univie.ac.at/ Your future tasks: Active participation in research, teaching and administration, which means: You develop your independent research
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/or observationally motivated model-building for SMBH feeding and feedback. The group integrates observations, theory, data analysis, algorithm development, model-building, and numerical simulations
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meetings Potentially participate in Arctic field campaigns Be working with large data sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit
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, engineers, and researchers in an effort to develop medical automation research solutions. You will support various engineering and computer science aspects of research projects focused on optimizing combat
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) Assessing the performance and fault tolerance of neuromorphic hardware; (b) Designing and developing one or more machine learning (ML) and artificial intelligence (AI) algorithms to support and enhance