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Field
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ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure
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to investigate the underlying DNA damage response mechanisms in cancers. One area of active research is to investigate mechanisms of sensing and resolving R-loops in cancers to provide molecular insight
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place to work. Our inclusive community of scholars, students, and staff impart an uncommon sense of larger purpose and contribute creative ideas to further the university's mission of teaching, discovery
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algorithm sensing, navigation and control of robot systems, including mobile robots and robot arms/manipulators; designing and implementing algorithms for machine learning, computer vision, and/or estimation
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models of surface change for comparison with morphometric analysis of visible remote-sensing observations of Mars and icy worlds Minimum Qualifications: PhD in engineering, planetary science or any related
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platforms for integrating spatial and temporal information, harnessing remote sensing data, using climate information, understanding fuel accumulation and running physics-based or data-driven wildfire
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familiarity with model coupling frameworks (e.g., ESMF). Proficiency in programming and data analysis (e.g., Python, Fortran) and handling large datasets, including GIS or remote sensing integration. Strong
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educational and research missions when all members of our community are able to leverage the experiences and ideas of others, embrace different viewpoints, feel that they belong, and know
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environmental stimulants. We employ an interdisciplinary approach to probe, model, and predict how signaling network dynamics translate extracellular cues sensed by GPCRs into specific phenotypic outputs
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or audio sensing). Experience in deploying research work on robot hardware. Strong communication skills (oral and written). Collaborative and team-oriented attitude. Completion of all doctoral