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are: i) to develop a new selected CI algorithm allowing reaching chemically-accurate results for large compounds; ii) to extend the currently-available database to properties relevant for both core
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to support a two-year Small Business Technology Transfer project (STTR) funded by the National Science Foundation. The successful candidate is expected to support the development, simulation and
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to contribute to cutting-edge research in robot intelligence, machine learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms
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responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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of Northeastern University's Experiential AI Institute, will lead the development and delivery of AI solutions across diverse industries. The role involves building end-to-end AI pipelines—from business problem
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exploratory analysis on large, multi-dimensional datasets; (b) develop predictive/diagnostic models and algorithms to lead and support clinical/translational research; (c) collaborate with cross-functional
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to support major transitions, train responsible engineers, and place scientific and technical excellence at the service of education, research, and innovation. As part of the France 2030 Superviz project
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of codes and algorithms. We will focus on devising computational solutions that can immediately be of use in other applications contexts as well. The candidate’s work will entail the development and
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monitoring. The visiting scholar intern will contribute to developing AI-enabled systems for plant health assessment, disease detection, and automated material handling. Major duties include: Design and
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machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in