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perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected
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of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values
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team and complete projects without constant supervision. Understanding the complexity of ecological data sets and the analysis thereof is essential to the project. Also, the integration of remote sensing
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systems, intelligent and autonomous systems; machine learning; environmental sensing; and wireless communications. The EE department has strong support from the College of Engineering and UTA administration
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 2 months ago
to artificial intelligence and machine learning, quantum information and sensing technologies, high-performance computing, communications technologies, semiconductors and microelectronics, biotechnology
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, students, and staff impart an uncommon sense of larger purpose and contribute creative ideas to further the university's mission of teaching, discovery, and engagement. Cornell’s regional and global presence
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healthy and cirrhotic human liver. Nature (2019). https://doi.org/10.1038/s41586-019-1670-9 PMID: 31645727 Values: We are committed to building a community where each of us can feel a sense of belonging
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on many-body phenomena relevant to near-term quantum platforms. Topics of research include but are not limited to the following: Quantum Dynamics, Topological Phases, and Quantum Sensing. Qualifications A
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-1670-9 PMID: 31645727 Values: We are committed to building a community where each of us can feel a sense of belonging, and where we can develop our own potential and the potential of our scholarship
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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